Transcriptome assembly and expression profiling of molecular responses to cadmium toxicity in hepatopancreas of the freshwater crab Sinopotamon henanense View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-05

AUTHORS

Min Sun, Yi Ting Li, Yang Liu, Shao Chin Lee, Lan Wang

ABSTRACT

Cadmium (Cd) pollution is a serious global problem, which causes irreversible toxic effects on animals. Freshwater crab, Sinopotamon henanense, is a useful environmental indicator since it is widely distributed in benthic habitats whereby it tends to accumulate Cd and other toxicants. However, its molecular responses to Cd toxicity remain unclear. In this study, we performed transcriptome sequencing and gene expression analyses of its hepatopancreas with and without Cd treatments. A total of 7.78 G clean reads were obtained from the pooled samples, and 68,648 unigenes with an average size of 622 bp were assembled, in which 5,436 were metabolism-associated and 2,728 were stimulus response-associated that include 380 immunity-related unigenes. Expression profile analysis demonstrated that most genes involved in macromolecular metabolism, oxidative phosphorylation, detoxification and anti-oxidant defense were up-regulated by Cd exposure, whereas immunity-related genes were down-regulated, except the genes involved in phagocytosis were up-regulated. The current data indicate that Cd exposure alters gene expressions in a concentration-dependent manner. Therefore, our results provide the first comprehensive S.henanense transcriptome dataset, which is useful for biological and ecotoxicological studies on this crab and its related species at molecular level, and some key Cd-responsive genes may provide candidate biomarkers for monitoring aquatic pollution by heavy metals. More... »

PAGES

19405

References to SciGraph publications

  • 2009-12. Validation of a primer optimisation matrix to improve the performance of reverse transcription – quantitative real-time PCR assays in BMC RESEARCH NOTES
  • 2015-09. Transcriptomic responses of corpuscle of Stannius gland of Japanese eels (Anguilla japonica) to Changes in Water Salinity in SCIENTIFIC REPORTS
  • 2010-12. MIQE précis: Practical implementation of minimum standard guidelines for fluorescence-based quantitative real-time PCR experiments in BMC MOLECULAR BIOLOGY
  • 2010-01. Sequencing technologies — the next generation in NATURE REVIEWS GENETICS
  • 2011-07. Full-length transcriptome assembly from RNA-Seq data without a reference genome in NATURE BIOTECHNOLOGY
  • 2008-07. Mapping and quantifying mammalian transcriptomes by RNA-Seq in NATURE METHODS
  • 2010-10. Cadmium stress: an oxidative challenge in BIOMETALS
  • 2008-07. Effects of Water-Borne Copper on Digestive and Metabolic Enzymes of the Giant Freshwater Prawn Macrobrachium rosenbergii in ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY
  • 2015-05. Novel transcriptome assembly and improved annotation of the whiteleg shrimp (Litopenaeus vannamei), a dominant crustacean in global seafood mariculture in SCIENTIFIC REPORTS
  • 2015-12. Complete depletion of primordial germ cells in an All-female fish leads to Sex-biased gene expression alteration and sterile All-male occurrence in BMC GENOMICS
  • 2015-11. Transcriptomic variation of hepatopancreas reveals the energy metabolism and biological processes associated with molting in Chinese mitten crab, Eriocheir sinensis in SCIENTIFIC REPORTS
  • 2009-12. Selection and validation of a set of reliable reference genes for quantitative RT-PCR studies in the brain of the Cephalopod Mollusc Octopus vulgaris in BMC MOLECULAR BIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/srep19405

    DOI

    http://dx.doi.org/10.1038/srep19405

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1047997121

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26786678


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Animals", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Brachyura", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cadmium", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Computational Biology", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Profiling", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Regulation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Ontology", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Hepatopancreas", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "High-Throughput Nucleotide Sequencing", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Molecular Sequence Annotation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Reproducibility of Results", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Transcriptome", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Water Pollutants, Chemical", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Shanxi University", 
              "id": "https://www.grid.ac/institutes/grid.163032.5", 
              "name": [
                "School of Life Science, Shanxi University, Taiyuan 030006, China."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sun", 
            "givenName": "Min", 
            "id": "sg:person.01344753256.78", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01344753256.78"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Shanxi University", 
              "id": "https://www.grid.ac/institutes/grid.163032.5", 
              "name": [
                "School of Life Science, Shanxi University, Taiyuan 030006, China."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ting Li", 
            "givenName": "Yi", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Shanxi University", 
              "id": "https://www.grid.ac/institutes/grid.163032.5", 
              "name": [
                "School of Life Science, Shanxi University, Taiyuan 030006, China."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Liu", 
            "givenName": "Yang", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Shanxi University", 
              "id": "https://www.grid.ac/institutes/grid.163032.5", 
              "name": [
                "School of Life Science, Shanxi University, Taiyuan 030006, China."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chin Lee", 
            "givenName": "Shao", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Shanxi University", 
              "id": "https://www.grid.ac/institutes/grid.163032.5", 
              "name": [
                "School of Life Science, Shanxi University, Taiyuan 030006, China."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wang", 
            "givenName": "Lan", 
            "id": "sg:person.0712247506.17", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0712247506.17"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.fsi.2012.08.027", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000296328"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.envres.2014.12.014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000604557"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.taap.2009.05.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001430553"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/es0630184", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002036921"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/es0630184", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002036921"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2199-10-70", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002974386", 
              "https://doi.org/10.1186/1471-2199-10-70"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.094482.109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003846316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.dci.2011.07.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005509289"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bti610", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006001436"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/tox.21817", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006054838"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1155/2014/903452", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006587250"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ecoenv.2012.10.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007425234"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/es4053363", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007470194"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1373/clinchem.2008.112797", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007780642"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1897/07-158r.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008091346"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.chemosphere.2008.09.025", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008365571"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.aquatox.2014.04.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010656911"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep09836", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011399581", 
              "https://doi.org/10.1038/srep09836"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.fsi.2010.06.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012179390"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-015-2130-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015781450", 
              "https://doi.org/10.1186/s12864-015-2130-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.1883", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015803168", 
              "https://doi.org/10.1038/nbt.1883"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.chemosphere.2014.11.046", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016424613"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.dci.2013.02.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018628083"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep14015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018804608", 
              "https://doi.org/10.1038/srep14015"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0068737", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019868042"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1756-0500-2-112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021315345", 
              "https://doi.org/10.1186/1756-0500-2-112"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1756-0500-2-112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021315345", 
              "https://doi.org/10.1186/1756-0500-2-112"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.fsi.2008.02.015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021402919"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0891-5849(94)00159-h", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023539488"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2626", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023911485", 
              "https://doi.org/10.1038/nrg2626"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2626", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023911485", 
              "https://doi.org/10.1038/nrg2626"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.mrfmmm.2003.07.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024422806"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0094055", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025261624"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0064485", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025528220"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.aquatox.2013.11.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026157657"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0047038", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027372775"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.fsi.2013.05.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028048018"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0084921", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028549900"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00244-007-9099-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028602992", 
              "https://doi.org/10.1007/s00244-007-9099-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00244-007-9099-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028602992", 
              "https://doi.org/10.1007/s00244-007-9099-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.chemosphere.2011.03.023", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031551425"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0027853", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033937091"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0089481", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034319333"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1214/aos/1013699998", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036427477"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0166-445x(00)00085-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036568609"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10534-010-9329-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037732668", 
              "https://doi.org/10.1007/s10534-010-9329-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10534-010-9329-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037732668", 
              "https://doi.org/10.1007/s10534-010-9329-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0145-305x(01)00018-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040867049"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cbpa.2012.12.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041705332"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.fsi.2010.08.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041710045"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/eesa.1996.0004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041856865"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep07081", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042790238", 
              "https://doi.org/10.1038/srep07081"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ecoenv.2005.10.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042897579"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp612", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043232906"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0068770", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043409021"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045381177", 
              "https://doi.org/10.1038/nmeth.1226"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0068233", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046339943"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0077569", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046496063"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0077569", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046496063"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0077569", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046496063"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2199-11-74", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050431407", 
              "https://doi.org/10.1186/1471-2199-11-74"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/9781848163324_0001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051271526"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.aquatox.2011.08.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052745360"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/es1037222", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055502537"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/es1037222", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055502537"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5271/sjweh.270", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1072737891"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1074631098", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.7.10.986", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083159139"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1083253857", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2016-05", 
        "datePublishedReg": "2016-05-01", 
        "description": "Cadmium (Cd) pollution is a serious global problem, which causes irreversible toxic effects on animals. Freshwater crab, Sinopotamon henanense, is a useful environmental indicator since it is widely distributed in benthic habitats whereby it tends to accumulate Cd and other toxicants. However, its molecular responses to Cd toxicity remain unclear. In this study, we performed transcriptome sequencing and gene expression analyses of its hepatopancreas with and without Cd treatments. A total of 7.78 G clean reads were obtained from the pooled samples, and 68,648 unigenes with an average size of 622 bp were assembled, in which 5,436 were metabolism-associated and 2,728 were stimulus response-associated that include 380 immunity-related unigenes. Expression profile analysis demonstrated that most genes involved in macromolecular metabolism, oxidative phosphorylation, detoxification and anti-oxidant defense were up-regulated by Cd exposure, whereas immunity-related genes were down-regulated, except the genes involved in phagocytosis were up-regulated. The current data indicate that Cd exposure alters gene expressions in a concentration-dependent manner. Therefore, our results provide the first comprehensive S.henanense transcriptome dataset, which is useful for biological and ecotoxicological studies on this crab and its related species at molecular level, and some key Cd-responsive genes may provide candidate biomarkers for monitoring aquatic pollution by heavy metals. ", 
        "genre": "research_article", 
        "id": "sg:pub.10.1038/srep19405", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1045337", 
            "issn": [
              "2045-2322"
            ], 
            "name": "Scientific Reports", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "6"
          }
        ], 
        "name": "Transcriptome assembly and expression profiling of molecular responses to cadmium toxicity in hepatopancreas of the freshwater crab Sinopotamon henanense", 
        "pagination": "19405", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "e4a6079255a690061dcdfffaf61fc23c7c5c55ec6efa434e8fe3bec496f1f573"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "26786678"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101563288"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/srep19405"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1047997121"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/srep19405", 
          "https://app.dimensions.ai/details/publication/pub.1047997121"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T23:32", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8693_00000551.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://www.nature.com/srep/2016/160120/srep19405/full/srep19405.html"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/srep19405'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/srep19405'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/srep19405'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/srep19405'


     

    This table displays all metadata directly associated to this object as RDF triples.

    338 TRIPLES      21 PREDICATES      103 URIs      34 LITERALS      22 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/srep19405 schema:about N124530c0d51d430eb61030a0a14dd515
    2 N12d4ef42b2c84152bc80c72c0e07d5eb
    3 N2f12a99186af4a40a428d74556e0995c
    4 N40650f47d71f4e33ada2414fb3849647
    5 N41deb115ef0d470c85811e7fbb03fe06
    6 N44f0caaf977344e5ad163afca42a4952
    7 N5abd7baac215472c8823b1a78d0bddc8
    8 N710b0ab96e754812832fb0f1099c2536
    9 N86a6f39344f548ae8c411a6bf6a30ba8
    10 Nb926d4dc2b984ae2ba9d985fdf5aa9f6
    11 Nd316527c62304100aae76151125daca8
    12 Ne70bd21d118a454b97a22cb2f392ca07
    13 Nf26e844480414810a12eae175b26d75c
    14 anzsrc-for:06
    15 anzsrc-for:0604
    16 schema:author N8abf7c360cb74ddf9e6b393ff7fb3216
    17 schema:citation sg:pub.10.1007/s00244-007-9099-9
    18 sg:pub.10.1007/s10534-010-9329-x
    19 sg:pub.10.1038/nbt.1883
    20 sg:pub.10.1038/nmeth.1226
    21 sg:pub.10.1038/nrg2626
    22 sg:pub.10.1038/srep07081
    23 sg:pub.10.1038/srep09836
    24 sg:pub.10.1038/srep14015
    25 sg:pub.10.1186/1471-2199-10-70
    26 sg:pub.10.1186/1471-2199-11-74
    27 sg:pub.10.1186/1756-0500-2-112
    28 sg:pub.10.1186/s12864-015-2130-z
    29 https://app.dimensions.ai/details/publication/pub.1074631098
    30 https://app.dimensions.ai/details/publication/pub.1083253857
    31 https://doi.org/10.1002/tox.21817
    32 https://doi.org/10.1006/eesa.1996.0004
    33 https://doi.org/10.1016/0891-5849(94)00159-h
    34 https://doi.org/10.1016/j.aquatox.2011.08.013
    35 https://doi.org/10.1016/j.aquatox.2013.11.022
    36 https://doi.org/10.1016/j.aquatox.2014.04.004
    37 https://doi.org/10.1016/j.cbpa.2012.12.008
    38 https://doi.org/10.1016/j.chemosphere.2008.09.025
    39 https://doi.org/10.1016/j.chemosphere.2011.03.023
    40 https://doi.org/10.1016/j.chemosphere.2014.11.046
    41 https://doi.org/10.1016/j.dci.2011.07.007
    42 https://doi.org/10.1016/j.dci.2013.02.009
    43 https://doi.org/10.1016/j.ecoenv.2005.10.012
    44 https://doi.org/10.1016/j.ecoenv.2012.10.022
    45 https://doi.org/10.1016/j.envres.2014.12.014
    46 https://doi.org/10.1016/j.fsi.2008.02.015
    47 https://doi.org/10.1016/j.fsi.2010.06.002
    48 https://doi.org/10.1016/j.fsi.2010.08.007
    49 https://doi.org/10.1016/j.fsi.2012.08.027
    50 https://doi.org/10.1016/j.fsi.2013.05.012
    51 https://doi.org/10.1016/j.mrfmmm.2003.07.011
    52 https://doi.org/10.1016/j.taap.2009.05.004
    53 https://doi.org/10.1016/s0145-305x(01)00018-0
    54 https://doi.org/10.1016/s0166-445x(00)00085-0
    55 https://doi.org/10.1021/es0630184
    56 https://doi.org/10.1021/es1037222
    57 https://doi.org/10.1021/es4053363
    58 https://doi.org/10.1093/bioinformatics/bti610
    59 https://doi.org/10.1093/bioinformatics/btp612
    60 https://doi.org/10.1101/gr.094482.109
    61 https://doi.org/10.1101/gr.7.10.986
    62 https://doi.org/10.1142/9781848163324_0001
    63 https://doi.org/10.1155/2014/903452
    64 https://doi.org/10.1214/aos/1013699998
    65 https://doi.org/10.1371/journal.pone.0027853
    66 https://doi.org/10.1371/journal.pone.0047038
    67 https://doi.org/10.1371/journal.pone.0064485
    68 https://doi.org/10.1371/journal.pone.0068233
    69 https://doi.org/10.1371/journal.pone.0068737
    70 https://doi.org/10.1371/journal.pone.0068770
    71 https://doi.org/10.1371/journal.pone.0077569
    72 https://doi.org/10.1371/journal.pone.0084921
    73 https://doi.org/10.1371/journal.pone.0089481
    74 https://doi.org/10.1371/journal.pone.0094055
    75 https://doi.org/10.1373/clinchem.2008.112797
    76 https://doi.org/10.1897/07-158r.1
    77 https://doi.org/10.5271/sjweh.270
    78 schema:datePublished 2016-05
    79 schema:datePublishedReg 2016-05-01
    80 schema:description Cadmium (Cd) pollution is a serious global problem, which causes irreversible toxic effects on animals. Freshwater crab, Sinopotamon henanense, is a useful environmental indicator since it is widely distributed in benthic habitats whereby it tends to accumulate Cd and other toxicants. However, its molecular responses to Cd toxicity remain unclear. In this study, we performed transcriptome sequencing and gene expression analyses of its hepatopancreas with and without Cd treatments. A total of 7.78 G clean reads were obtained from the pooled samples, and 68,648 unigenes with an average size of 622 bp were assembled, in which 5,436 were metabolism-associated and 2,728 were stimulus response-associated that include 380 immunity-related unigenes. Expression profile analysis demonstrated that most genes involved in macromolecular metabolism, oxidative phosphorylation, detoxification and anti-oxidant defense were up-regulated by Cd exposure, whereas immunity-related genes were down-regulated, except the genes involved in phagocytosis were up-regulated. The current data indicate that Cd exposure alters gene expressions in a concentration-dependent manner. Therefore, our results provide the first comprehensive S.henanense transcriptome dataset, which is useful for biological and ecotoxicological studies on this crab and its related species at molecular level, and some key Cd-responsive genes may provide candidate biomarkers for monitoring aquatic pollution by heavy metals.
    81 schema:genre research_article
    82 schema:inLanguage en
    83 schema:isAccessibleForFree true
    84 schema:isPartOf N2cfa713430df4bef843850bd30e313a4
    85 Nba943e8d61de40648b0c01622eb9386b
    86 sg:journal.1045337
    87 schema:name Transcriptome assembly and expression profiling of molecular responses to cadmium toxicity in hepatopancreas of the freshwater crab Sinopotamon henanense
    88 schema:pagination 19405
    89 schema:productId N26e6972f4f6c404b94b176c999fd6cdc
    90 N44807abcd2424c5397f7ecc33e827e00
    91 Nb335db9a27834d328a8ec5457f3e7be6
    92 Ne7a4b91c18514f469447a1b48b867c94
    93 Nf15bb7199f75470fb420a3ac6a3d9fd3
    94 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047997121
    95 https://doi.org/10.1038/srep19405
    96 schema:sdDatePublished 2019-04-10T23:32
    97 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    98 schema:sdPublisher Nfe49e9876ba84bd2a45030db54cf1558
    99 schema:url http://www.nature.com/srep/2016/160120/srep19405/full/srep19405.html
    100 sgo:license sg:explorer/license/
    101 sgo:sdDataset articles
    102 rdf:type schema:ScholarlyArticle
    103 N124530c0d51d430eb61030a0a14dd515 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    104 schema:name Molecular Sequence Annotation
    105 rdf:type schema:DefinedTerm
    106 N12d4ef42b2c84152bc80c72c0e07d5eb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    107 schema:name Reproducibility of Results
    108 rdf:type schema:DefinedTerm
    109 N259e7207de2447ca8f54f019bded15e8 schema:affiliation https://www.grid.ac/institutes/grid.163032.5
    110 schema:familyName Ting Li
    111 schema:givenName Yi
    112 rdf:type schema:Person
    113 N26e6972f4f6c404b94b176c999fd6cdc schema:name dimensions_id
    114 schema:value pub.1047997121
    115 rdf:type schema:PropertyValue
    116 N2cfa713430df4bef843850bd30e313a4 schema:volumeNumber 6
    117 rdf:type schema:PublicationVolume
    118 N2f12a99186af4a40a428d74556e0995c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    119 schema:name Gene Expression Regulation
    120 rdf:type schema:DefinedTerm
    121 N40650f47d71f4e33ada2414fb3849647 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    122 schema:name Brachyura
    123 rdf:type schema:DefinedTerm
    124 N41deb115ef0d470c85811e7fbb03fe06 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    125 schema:name Animals
    126 rdf:type schema:DefinedTerm
    127 N44807abcd2424c5397f7ecc33e827e00 schema:name nlm_unique_id
    128 schema:value 101563288
    129 rdf:type schema:PropertyValue
    130 N44f0caaf977344e5ad163afca42a4952 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    131 schema:name Hepatopancreas
    132 rdf:type schema:DefinedTerm
    133 N5abd7baac215472c8823b1a78d0bddc8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    134 schema:name Cadmium
    135 rdf:type schema:DefinedTerm
    136 N710b0ab96e754812832fb0f1099c2536 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    137 schema:name Water Pollutants, Chemical
    138 rdf:type schema:DefinedTerm
    139 N86a6f39344f548ae8c411a6bf6a30ba8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    140 schema:name Gene Ontology
    141 rdf:type schema:DefinedTerm
    142 N8ab95aae86ce441698e31b44f5b79e2c rdf:first sg:person.0712247506.17
    143 rdf:rest rdf:nil
    144 N8abf7c360cb74ddf9e6b393ff7fb3216 rdf:first sg:person.01344753256.78
    145 rdf:rest Nf91a8d030e944d7e856255d10993fa65
    146 N9dbf5ec1308c4ee39ba8a8c4f7086a94 rdf:first Nde8051cfb194477bb0fec469ec51cda0
    147 rdf:rest N8ab95aae86ce441698e31b44f5b79e2c
    148 Nb0aa0764e52b477281b2b299a6d95a33 rdf:first Ndcdca34b346c4836bd1b34b22aca1e2f
    149 rdf:rest N9dbf5ec1308c4ee39ba8a8c4f7086a94
    150 Nb335db9a27834d328a8ec5457f3e7be6 schema:name pubmed_id
    151 schema:value 26786678
    152 rdf:type schema:PropertyValue
    153 Nb926d4dc2b984ae2ba9d985fdf5aa9f6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    154 schema:name Computational Biology
    155 rdf:type schema:DefinedTerm
    156 Nba943e8d61de40648b0c01622eb9386b schema:issueNumber 1
    157 rdf:type schema:PublicationIssue
    158 Nd316527c62304100aae76151125daca8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    159 schema:name High-Throughput Nucleotide Sequencing
    160 rdf:type schema:DefinedTerm
    161 Ndcdca34b346c4836bd1b34b22aca1e2f schema:affiliation https://www.grid.ac/institutes/grid.163032.5
    162 schema:familyName Liu
    163 schema:givenName Yang
    164 rdf:type schema:Person
    165 Nde8051cfb194477bb0fec469ec51cda0 schema:affiliation https://www.grid.ac/institutes/grid.163032.5
    166 schema:familyName Chin Lee
    167 schema:givenName Shao
    168 rdf:type schema:Person
    169 Ne70bd21d118a454b97a22cb2f392ca07 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    170 schema:name Gene Expression Profiling
    171 rdf:type schema:DefinedTerm
    172 Ne7a4b91c18514f469447a1b48b867c94 schema:name readcube_id
    173 schema:value e4a6079255a690061dcdfffaf61fc23c7c5c55ec6efa434e8fe3bec496f1f573
    174 rdf:type schema:PropertyValue
    175 Nf15bb7199f75470fb420a3ac6a3d9fd3 schema:name doi
    176 schema:value 10.1038/srep19405
    177 rdf:type schema:PropertyValue
    178 Nf26e844480414810a12eae175b26d75c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    179 schema:name Transcriptome
    180 rdf:type schema:DefinedTerm
    181 Nf91a8d030e944d7e856255d10993fa65 rdf:first N259e7207de2447ca8f54f019bded15e8
    182 rdf:rest Nb0aa0764e52b477281b2b299a6d95a33
    183 Nfe49e9876ba84bd2a45030db54cf1558 schema:name Springer Nature - SN SciGraph project
    184 rdf:type schema:Organization
    185 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    186 schema:name Biological Sciences
    187 rdf:type schema:DefinedTerm
    188 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    189 schema:name Genetics
    190 rdf:type schema:DefinedTerm
    191 sg:journal.1045337 schema:issn 2045-2322
    192 schema:name Scientific Reports
    193 rdf:type schema:Periodical
    194 sg:person.01344753256.78 schema:affiliation https://www.grid.ac/institutes/grid.163032.5
    195 schema:familyName Sun
    196 schema:givenName Min
    197 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01344753256.78
    198 rdf:type schema:Person
    199 sg:person.0712247506.17 schema:affiliation https://www.grid.ac/institutes/grid.163032.5
    200 schema:familyName Wang
    201 schema:givenName Lan
    202 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0712247506.17
    203 rdf:type schema:Person
    204 sg:pub.10.1007/s00244-007-9099-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028602992
    205 https://doi.org/10.1007/s00244-007-9099-9
    206 rdf:type schema:CreativeWork
    207 sg:pub.10.1007/s10534-010-9329-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1037732668
    208 https://doi.org/10.1007/s10534-010-9329-x
    209 rdf:type schema:CreativeWork
    210 sg:pub.10.1038/nbt.1883 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015803168
    211 https://doi.org/10.1038/nbt.1883
    212 rdf:type schema:CreativeWork
    213 sg:pub.10.1038/nmeth.1226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045381177
    214 https://doi.org/10.1038/nmeth.1226
    215 rdf:type schema:CreativeWork
    216 sg:pub.10.1038/nrg2626 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023911485
    217 https://doi.org/10.1038/nrg2626
    218 rdf:type schema:CreativeWork
    219 sg:pub.10.1038/srep07081 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042790238
    220 https://doi.org/10.1038/srep07081
    221 rdf:type schema:CreativeWork
    222 sg:pub.10.1038/srep09836 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011399581
    223 https://doi.org/10.1038/srep09836
    224 rdf:type schema:CreativeWork
    225 sg:pub.10.1038/srep14015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018804608
    226 https://doi.org/10.1038/srep14015
    227 rdf:type schema:CreativeWork
    228 sg:pub.10.1186/1471-2199-10-70 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002974386
    229 https://doi.org/10.1186/1471-2199-10-70
    230 rdf:type schema:CreativeWork
    231 sg:pub.10.1186/1471-2199-11-74 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050431407
    232 https://doi.org/10.1186/1471-2199-11-74
    233 rdf:type schema:CreativeWork
    234 sg:pub.10.1186/1756-0500-2-112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021315345
    235 https://doi.org/10.1186/1756-0500-2-112
    236 rdf:type schema:CreativeWork
    237 sg:pub.10.1186/s12864-015-2130-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1015781450
    238 https://doi.org/10.1186/s12864-015-2130-z
    239 rdf:type schema:CreativeWork
    240 https://app.dimensions.ai/details/publication/pub.1074631098 schema:CreativeWork
    241 https://app.dimensions.ai/details/publication/pub.1083253857 schema:CreativeWork
    242 https://doi.org/10.1002/tox.21817 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006054838
    243 rdf:type schema:CreativeWork
    244 https://doi.org/10.1006/eesa.1996.0004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041856865
    245 rdf:type schema:CreativeWork
    246 https://doi.org/10.1016/0891-5849(94)00159-h schema:sameAs https://app.dimensions.ai/details/publication/pub.1023539488
    247 rdf:type schema:CreativeWork
    248 https://doi.org/10.1016/j.aquatox.2011.08.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052745360
    249 rdf:type schema:CreativeWork
    250 https://doi.org/10.1016/j.aquatox.2013.11.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026157657
    251 rdf:type schema:CreativeWork
    252 https://doi.org/10.1016/j.aquatox.2014.04.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010656911
    253 rdf:type schema:CreativeWork
    254 https://doi.org/10.1016/j.cbpa.2012.12.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041705332
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1016/j.chemosphere.2008.09.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008365571
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.1016/j.chemosphere.2011.03.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031551425
    259 rdf:type schema:CreativeWork
    260 https://doi.org/10.1016/j.chemosphere.2014.11.046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016424613
    261 rdf:type schema:CreativeWork
    262 https://doi.org/10.1016/j.dci.2011.07.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005509289
    263 rdf:type schema:CreativeWork
    264 https://doi.org/10.1016/j.dci.2013.02.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018628083
    265 rdf:type schema:CreativeWork
    266 https://doi.org/10.1016/j.ecoenv.2005.10.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042897579
    267 rdf:type schema:CreativeWork
    268 https://doi.org/10.1016/j.ecoenv.2012.10.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007425234
    269 rdf:type schema:CreativeWork
    270 https://doi.org/10.1016/j.envres.2014.12.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000604557
    271 rdf:type schema:CreativeWork
    272 https://doi.org/10.1016/j.fsi.2008.02.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021402919
    273 rdf:type schema:CreativeWork
    274 https://doi.org/10.1016/j.fsi.2010.06.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012179390
    275 rdf:type schema:CreativeWork
    276 https://doi.org/10.1016/j.fsi.2010.08.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041710045
    277 rdf:type schema:CreativeWork
    278 https://doi.org/10.1016/j.fsi.2012.08.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000296328
    279 rdf:type schema:CreativeWork
    280 https://doi.org/10.1016/j.fsi.2013.05.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028048018
    281 rdf:type schema:CreativeWork
    282 https://doi.org/10.1016/j.mrfmmm.2003.07.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024422806
    283 rdf:type schema:CreativeWork
    284 https://doi.org/10.1016/j.taap.2009.05.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001430553
    285 rdf:type schema:CreativeWork
    286 https://doi.org/10.1016/s0145-305x(01)00018-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040867049
    287 rdf:type schema:CreativeWork
    288 https://doi.org/10.1016/s0166-445x(00)00085-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036568609
    289 rdf:type schema:CreativeWork
    290 https://doi.org/10.1021/es0630184 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002036921
    291 rdf:type schema:CreativeWork
    292 https://doi.org/10.1021/es1037222 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055502537
    293 rdf:type schema:CreativeWork
    294 https://doi.org/10.1021/es4053363 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007470194
    295 rdf:type schema:CreativeWork
    296 https://doi.org/10.1093/bioinformatics/bti610 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006001436
    297 rdf:type schema:CreativeWork
    298 https://doi.org/10.1093/bioinformatics/btp612 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043232906
    299 rdf:type schema:CreativeWork
    300 https://doi.org/10.1101/gr.094482.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003846316
    301 rdf:type schema:CreativeWork
    302 https://doi.org/10.1101/gr.7.10.986 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083159139
    303 rdf:type schema:CreativeWork
    304 https://doi.org/10.1142/9781848163324_0001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051271526
    305 rdf:type schema:CreativeWork
    306 https://doi.org/10.1155/2014/903452 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006587250
    307 rdf:type schema:CreativeWork
    308 https://doi.org/10.1214/aos/1013699998 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036427477
    309 rdf:type schema:CreativeWork
    310 https://doi.org/10.1371/journal.pone.0027853 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033937091
    311 rdf:type schema:CreativeWork
    312 https://doi.org/10.1371/journal.pone.0047038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027372775
    313 rdf:type schema:CreativeWork
    314 https://doi.org/10.1371/journal.pone.0064485 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025528220
    315 rdf:type schema:CreativeWork
    316 https://doi.org/10.1371/journal.pone.0068233 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046339943
    317 rdf:type schema:CreativeWork
    318 https://doi.org/10.1371/journal.pone.0068737 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019868042
    319 rdf:type schema:CreativeWork
    320 https://doi.org/10.1371/journal.pone.0068770 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043409021
    321 rdf:type schema:CreativeWork
    322 https://doi.org/10.1371/journal.pone.0077569 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046496063
    323 rdf:type schema:CreativeWork
    324 https://doi.org/10.1371/journal.pone.0084921 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028549900
    325 rdf:type schema:CreativeWork
    326 https://doi.org/10.1371/journal.pone.0089481 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034319333
    327 rdf:type schema:CreativeWork
    328 https://doi.org/10.1371/journal.pone.0094055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025261624
    329 rdf:type schema:CreativeWork
    330 https://doi.org/10.1373/clinchem.2008.112797 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007780642
    331 rdf:type schema:CreativeWork
    332 https://doi.org/10.1897/07-158r.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008091346
    333 rdf:type schema:CreativeWork
    334 https://doi.org/10.5271/sjweh.270 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072737891
    335 rdf:type schema:CreativeWork
    336 https://www.grid.ac/institutes/grid.163032.5 schema:alternateName Shanxi University
    337 schema:name School of Life Science, Shanxi University, Taiyuan 030006, China.
    338 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...