{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:11:01Z","timestamp":1760235061808,"version":"build-2065373602"},"reference-count":58,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Publicly available RNA-sequencing (RNA-seq) data are a rich resource for elucidating the mechanisms of human disease; however, preprocessing these data requires considerable bioinformatic expertise and computational infrastructure. Analyzing multiple datasets with a consistent computational workflow increases the accuracy of downstream meta-analyses. This collection of datasets represents the human intracellular transcriptional response to disorders and diseases such as acute lymphoblastic leukemia (ALL), B-cell lymphomas, chronic obstructive pulmonary disease (COPD), colorectal cancer, lupus erythematosus; as well as infection with pathogens including Borrelia burgdorferi, hantavirus, influenza A virus, Middle East respiratory syndrome coronavirus (MERS-CoV), Streptococcus pneumoniae, respiratory syncytial virus (RSV), severe acute respiratory syndrome coronavirus (SARS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We calculated the statistically significant differentially expressed genes and Gene Ontology terms for all datasets. In addition, a subset of the datasets also includes results from splice variant analyses, intracellular signaling pathway enrichments as well as read mapping and quantification. All analyses were performed using well-established algorithms and are provided to facilitate future data mining activities, wet lab studies, and to accelerate collaboration and discovery.<\/jats:p>","DOI":"10.3390\/data6070075","type":"journal-article","created":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T02:52:34Z","timestamp":1626317554000},"page":"75","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Preprocessing of Public RNA-Sequencing Datasets to Facilitate Downstream Analyses of Human Diseases"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4759-7863","authenticated-orcid":false,"given":"Naomi","family":"Rapier-Sharman","sequence":"first","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"given":"John","family":"Krapohl","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"given":"Ethan J.","family":"Beausoleil","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"given":"Kennedy T. L.","family":"Gifford","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"given":"Benjamin R.","family":"Hinatsu","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"given":"Curtis S.","family":"Hoffmann","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"given":"Makayla","family":"Komer","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6209-8301","authenticated-orcid":false,"given":"Tiana M.","family":"Scott","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7930-8160","authenticated-orcid":false,"given":"Brett E.","family":"Pickett","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.1093\/bioinformatics\/bty825","article-title":"MetaOmics: Analysis Pipeline and Browser-Based Software Suite for Transcriptomic Meta-Analysis","volume":"35","author":"Ma","year":"2019","journal-title":"Bioinformatics"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1093\/bioinformatics\/btu679","article-title":"JNMFMA: A Joint Non-Negative Matrix Factorization Meta-Analysis of Transcriptomics Data","volume":"31","author":"Wang","year":"2015","journal-title":"Bioinformatics"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Menon, R., Garg, G., Gasser, R.B., and Ranganathan, S. (2012). TranSeqAnnotator: Large-Scale Analysis of Transcriptomic Data. BMC Bioinform., 13.","DOI":"10.1186\/1471-2105-13-S17-S24"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1186\/s13059-021-02290-6","article-title":"A Benchmark for RNA-Seq Deconvolution Analysis under Dynamic Testing Environments","volume":"22","author":"Jin","year":"2021","journal-title":"Genome Biol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"W210","DOI":"10.1093\/nar\/gkq388","article-title":"Babelomics: An Integrative Platform for the Analysis of Transcriptomics, Proteomics and Genomic Data with Advanced Functional Profiling","volume":"38","author":"Medina","year":"2010","journal-title":"Nucleic Acids Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"5717","DOI":"10.1158\/1078-0432.CCR-19-1131","article-title":"Prognostic Implications of PD-L1 Expression in Breast Cancer: Systematic Review and Meta-Analysis of Immunohistochemistry and Pooled Analysis of Transcriptomic Data","volume":"25","author":"Matikas","year":"2019","journal-title":"Clin. Cancer Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1007\/s40291-020-00497-0","article-title":"Meta-Analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation","volume":"24","year":"2020","journal-title":"Mol. Diagn. Ther."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"140033","DOI":"10.1038\/sdata.2014.33","article-title":"A Comprehensive Collection of Systems Biology Data Characterizing the Host Response to Viral Infection","volume":"1","author":"Aevermann","year":"2014","journal-title":"Sci. Data"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kori, M., and Yalcin Arga, K. (2018). Potential Biomarkers and Therapeutic Targets in Cervical Cancer: Insights from the Meta-Analysis of Transcriptomics Data within Network Biomedicine Perspective. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0200717"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1635","DOI":"10.3233\/JAD-181085","article-title":"A Meta-Analysis of Alzheimer\u2019s Disease Brain Transcriptomic Data","volume":"68","author":"Patel","year":"2019","journal-title":"J. Alzheimers Dis."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1186\/s12967-017-1294-5","article-title":"Transcriptomic Meta-Analysis Identifies Gene Expression Characteristics in Various Samples of HIV-Infected Patients with Nonprogressive Disease","volume":"15","author":"Zhang","year":"2017","journal-title":"J. Transl. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"160018","DOI":"10.1038\/sdata.2016.18","article-title":"The FAIR Guiding Principles for Scientific Data Management and Stewardship","volume":"3","author":"Wilkinson","year":"2016","journal-title":"Sci. Data"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1038\/nbt.1411","article-title":"Promoting Coherent Minimum Reporting Guidelines for Biological and Biomedical Investigations: The MIBBI Project","volume":"26","author":"Taylor","year":"2008","journal-title":"Nat. Biotechnol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"35","DOI":"10.31989\/ffhd.v2i3.100","article-title":"Glycophospholipid Formulation with NADH and CoQ10 Significantly Reduces Intractable Fatigue in Western Blot-Positive \u2018Chronic Lyme Disease\u2019 Patients: Preliminary Report","volume":"2","author":"Nicolson","year":"2012","journal-title":"Funct. Foods Health Dis."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"369","DOI":"10.2174\/157339706778699850","article-title":"Clinical Features of Scleroderma-Like Disorders: A Challenge for the Rheumatologist","volume":"2","author":"Czirjak","year":"2006","journal-title":"Curr. Rheumatol. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3233\/JND-200518","article-title":"Orphan Peripheral Neuropathies","volume":"8","author":"Finsterer","year":"2021","journal-title":"J. Neuromuscul. Dis."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3428","DOI":"10.1128\/JVI.02695-15","article-title":"ISG15 Is Upregulated in Respiratory Syncytial Virus Infection and Reduces Virus Growth through Protein ISGylation","volume":"90","author":"Mata","year":"2016","journal-title":"J. Virol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Drori, Y., Jacob-Hirsch, J., Pando, R., Glatman-Freedman, A., Friedman, N., Mendelson, E., and Mandelboim, M. (2020). Influenza A Virus Inhibits RSV Infection via a Two-Wave Expression of IFIT Proteins. Viruses, 12.","DOI":"10.3390\/v12101171"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1038\/ni.3279","article-title":"PARP9-DTX3L Ubiquitin Ligase Targets Host Histone H2BJ and Viral 3C Protease to Enhance Interferon Signaling and Control Viral Infection","volume":"16","author":"Zhang","year":"2015","journal-title":"Nat. Immunol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.biopha.2018.07.171","article-title":"CXCL9 Promotes the Progression of Diffuse Large B-Cell Lymphoma through up-Regulating \u03b2-Catenin","volume":"107","author":"Ruiduo","year":"2018","journal-title":"Biomed. Pharmacother."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"50","DOI":"10.3109\/10428194.2011.616611","article-title":"Prognostic Value of Serum CD44, Intercellular Adhesion Molecule-1 and Vascular Cell Adhesion Molecule-1 Levels in Patients with Indolent Non-Hodgkin Lymphomas","volume":"53","author":"Shah","year":"2012","journal-title":"Leuk. Lymphoma"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1440","DOI":"10.1158\/2159-8290.CD-20-1465","article-title":"Venetoclax and Navitoclax in Combination with Chemotherapy in Patients with Relapsed or Refractory Acute Lymphoblastic Leukemia and Lymphoblastic Lymphoma","volume":"11","author":"Pullarkat","year":"2021","journal-title":"Cancer Discov."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"4823","DOI":"10.1158\/1078-0432.CCR-20-1434","article-title":"Tumor Microenvironment Composition and Severe Cytokine Release Syndrome (CRS) Influence Toxicity in Patients with Large B-Cell Lymphoma Treated with Axicabtagene Ciloleucel","volume":"26","author":"Faramand","year":"2020","journal-title":"Clin. Cancer Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1016\/j.ccell.2019.05.002","article-title":"Non-Oncogene Addiction to SIRT3 Plays a Critical Role in Lymphomagenesis","volume":"35","author":"Li","year":"2019","journal-title":"Cancer Cell"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1182\/blood-2017-10-810739","article-title":"Aggressive B-Cell Lymphomas in Patients with Myelofibrosis Receiving JAK1\/2 Inhibitor Therapy","volume":"132","author":"Porpaczy","year":"2018","journal-title":"Blood"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1038\/s41467-017-02595-w","article-title":"AICDA Drives Epigenetic Heterogeneity and Accelerates Germinal Center-Derived Lymphomagenesis","volume":"9","author":"Teater","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4805","DOI":"10.4049\/jimmunol.1501982","article-title":"NKG2D-NKG2D Ligand Interaction Inhibits the outgrowth of Naturally Arising Low-Grade B Cell Lymphoma In Vivo","volume":"196","author":"Raju","year":"2016","journal-title":"J. Immunol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Rouhigharabaei, L., Finalet Ferreiro, J., Tousseyn, T., van der Krogt, J.-A., Put, N., Haralambieva, E., Graux, C., Maes, B., Vicente, C., and Vandenberghe, P. (2014). Non-IG Aberrations of FOXP1 in B-Cell Malignancies Lead to an Aberrant Expression of N-Truncated Isoforms of FOXP1. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0085851"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1186\/s13073-015-0230-7","article-title":"Transcriptome Sequencing Reveals Thousands of Novel Long Non-Coding RNAs in B Cell Lymphoma","volume":"7","author":"Verma","year":"2015","journal-title":"Genome Med."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"e00100","DOI":"10.1128\/mBio.00100-16","article-title":"Longitudinal Transcriptome Analysis Reveals a Sustained Differential Gene Expression Signature in Patients Treated for Acute Lyme Disease","volume":"7","author":"Bouquet","year":"2016","journal-title":"MBio"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2643","DOI":"10.2147\/COPD.S166812","article-title":"Gene Expression Profile of Human Lung in a Relatively Early Stage of COPD with Emphysema","volume":"13","author":"Jeong","year":"2018","journal-title":"Int. J. Chronic Obstr. Pulm. Dis."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4650","DOI":"10.1002\/cam4.1696","article-title":"Differentially Expressed LncRNAs and MRNAs Identified by NGS Analysis in Colorectal Cancer Patients","volume":"7","author":"Li","year":"2018","journal-title":"Cancer Med."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"265","DOI":"10.7150\/thno.36045","article-title":"Long Noncoding RNA PiHL Regulates P53 Protein Stability through GRWD1\/RPL11\/MDM2 Axis in Colorectal Cancer","volume":"10","author":"Deng","year":"2020","journal-title":"Theranostics"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Lazar, S.B., Pongor, L., Li, X.L., Grammatikakis, I., Muys, B.R., Dangelmaier, E.A., Redon, C.E., Jang, S.-M., Walker, R.L., and Tang, W. (2020). Genome-Wide Analysis of the FOXA1 Transcriptional Network Identifies Novel Protein-Coding and Long Noncoding RNA Targets in Colorectal Cancer Cells. Mol. Cell. Biol., 40.","DOI":"10.1128\/MCB.00224-20"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"97","DOI":"10.3389\/fcimb.2020.00097","article-title":"RNA-Seq Revealed a Circular RNA-MicroRNA-MRNA Regulatory Network in Hantaan Virus Infection","volume":"10","author":"Lu","year":"2020","journal-title":"Front. Cell. Infect. Microbiol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2303","DOI":"10.1080\/22221751.2020.1830717","article-title":"Rapid Humoral Immune Responses Are Required for Recovery from Haemorrhagic Fever with Renal Syndrome Patients","volume":"9","author":"Li","year":"2020","journal-title":"Emerg. Microbes Infect."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1036","DOI":"10.1016\/j.cell.2020.04.026","article-title":"Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19","volume":"181","author":"Liu","year":"2020","journal-title":"Cell"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1016\/j.immuni.2018.08.015","article-title":"Distinct Effector B Cells Induced by Unregulated Toll-like Receptor 7 Contribute to Pathogenic Responses in Systemic Lupus Erythematosus","volume":"49","author":"Jenks","year":"2018","journal-title":"Immunity"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1038\/s41590-019-0419-9","article-title":"Epigenetic Programming Underpins B Cell Dysfunction in Human SLE","volume":"20","author":"Scharer","year":"2019","journal-title":"Nat. Immunol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.1038\/s41467-018-03750-7","article-title":"IL-21 Drives Expansion and Plasma Cell Differentiation of Autoreactive CD11chiT-Bet+ B Cells in SLE","volume":"9","author":"Wang","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1080\/22221751.2020.1738277","article-title":"Competing Endogenous RNA Network Profiling Reveals Novel Host Dependency Factors Required for MERS-CoV Propagation","volume":"9","author":"Zhang","year":"2020","journal-title":"Emerg. Microbes Infect."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1038\/s41467-018-08015-x","article-title":"SREBP-Dependent Lipidomic Reprogramming as a Broad-Spectrum Antiviral Target","volume":"10","author":"Yuan","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1186\/s13059-016-1054-5","article-title":"Time-Resolved Dual RNA-Seq Reveals Extensive Rewiring of Lung Epithelial and Pneumococcal Transcriptomes during Early Infection","volume":"17","author":"Aprianto","year":"2016","journal-title":"Genome Biol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kuipers, K., Lokken, K.L., Zangari, T., Boyer, M.A., Shin, S., and Weiser, J.N. (2018). Age-Related Differences in IL-1 Signaling and Capsule Serotype Affect Persistence of Streptococcus Pneumoniae Colonization. PLoS Pathog., 14.","DOI":"10.1371\/journal.ppat.1007396"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1038\/s41590-018-0231-y","article-title":"Inflammation Induced by Influenza Virus Impairs Human Innate Immune Control of Pneumococcus","volume":"19","author":"Jochems","year":"2018","journal-title":"Nat. Immunol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3060","DOI":"10.1038\/s41467-019-11005-2","article-title":"Microinvasion by Streptococcus Pneumoniae Induces Epithelial Innate Immunity during Colonisation at the Human Mucosal Surface","volume":"10","author":"Weight","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1126\/science.abc1669","article-title":"SARS-CoV-2 Productively Infects Human Gut Enterocytes","volume":"369","author":"Lamers","year":"2020","journal-title":"Science"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Duan, F., Guo, L., Yang, L., Han, Y., Thakur, A., Nilsson-Payant, B.E., Wang, P., Zhang, Z., Ma, C.Y., and Zhou, X. (2020). Modeling COVID-19 with Human Pluripotent Stem Cell-Derived Cells Reveals Synergistic Effects of Anti-Inflammatory Macrophages with ACE2 Inhibition Against SARS-CoV-2. Res. Sq.","DOI":"10.21203\/rs.3.rs-62758\/v1"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Vanderheiden, A., Ralfs, P., Chirkova, T., Upadhyay, A.A., Zimmerman, M.G., Bedoya, S., Aoued, H., Tharp, G.M., Pellegrini, K.L., and Manfredi, C. (2020). Type I and Type III Interferons Restrict SARS-CoV-2 Infection of Human Airway Epithelial Cultures. J. Virol., 94.","DOI":"10.1128\/JVI.00985-20"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2089","DOI":"10.1534\/g3.119.400185","article-title":"ARMOR: An Automated Reproducible MOdular Workflow for Preprocessing and Differential Analysis of RNA-Seq Data","volume":"9","author":"Orjuela","year":"2019","journal-title":"G3 Genes Genomes Genet."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2520","DOI":"10.1093\/bioinformatics\/bts480","article-title":"Snakemake\u2014A Scalable Bioinformatics Workflow Engine","volume":"28","author":"Rahmann","year":"2012","journal-title":"Bioinformatics"},{"key":"ref_52","unstructured":"(2021, June 07). Babraham Bioinformatics\u2014Trim Galore!. Available online: https:\/\/www.bioinformatics.babraham.ac.uk\/projects\/trim_galore\/."},{"key":"ref_53","unstructured":"(2021, June 07). Babraham Bioinformatics\u2014FastQC A Quality Control Tool for High Throughput Sequence Data. Available online: https:\/\/www.bioinformatics.babraham.ac.uk\/projects\/fastqc\/."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1038\/nmeth.4197","article-title":"Salmon Provides Fast and Bias-Aware Quantification of Transcript Expression","volume":"14","author":"Patro","year":"2017","journal-title":"Nat. Methods"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1093\/bioinformatics\/btp616","article-title":"EdgeR: A Bioconductor Package for Differential Expression Analysis of Digital Gene Expression Data","volume":"26","author":"Robinson","year":"2010","journal-title":"Bioinformatics"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"e133","DOI":"10.1093\/nar\/gks461","article-title":"Camera: A Competitive Gene Set Test Accounting for Inter-Gene Correlation","volume":"40","author":"Wu","year":"2012","journal-title":"Nucleic Acids Res."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.12688\/f1000research.8900.2","article-title":"DRIMSeq: A Dirichlet-Multinomial Framework for Multivariate Count Outcomes in Genomics","volume":"5","author":"Nowicka","year":"2016","journal-title":"F1000Research"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1093\/bioinformatics\/btn577","article-title":"A Novel Signaling Pathway Impact Analysis","volume":"25","author":"Tarca","year":"2009","journal-title":"Bioinformatics"}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/7\/75\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:30:48Z","timestamp":1760164248000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/7\/75"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,15]]},"references-count":58,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["data6070075"],"URL":"https:\/\/doi.org\/10.3390\/data6070075","relation":{},"ISSN":["2306-5729"],"issn-type":[{"type":"electronic","value":"2306-5729"}],"subject":[],"published":{"date-parts":[[2021,7,15]]}}}