Gene Expression Omnibus: NCBI gene expression and hybridization array data repository

Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray

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Serial Analysis of Gene Expression

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Gene expression informatics —it's all in your mine

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Using oligonucleotide probe arrays to access genetic diversity

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One-stop shop for microarray data

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Unlimited Access—Limitless SuccessPreprint

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Inferring tumour purity and stromal and immune cell admixture from expression data

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Database resources of the National Center for Biotechnology Information: update

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NCBI GEO: archive for functional genomics data sets—update

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Scenic: single-cell regulatory network inference and clustering.

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Gene set knowledge discovery with enrichr

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A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles

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A gene atlas of the mouse and human protein-encoding transcriptomes

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DNA methylation-based biomarkers and the epigenetic clock theory of ageing

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miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades

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Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases

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Genomic responses in mouse models poorly mimic human inflammatory diseases

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Leukemic IDH1 and IDH2 Mutations Result in a Hypermethylation Phenotype, Disrupt TET2 Function, and Impair Hematopoietic Differentiation

Figueroa, M. E., Abdel-Wahab, O., Lu, C., Ward, P. S., Patel, J., Shih, A., Li, Y., Bhagwat, N., Vasanthakumar, A., Fernandez, H. F., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.11.015 · Cited by 2,766

An “Electronic Fluorescent Pictograph” Browser for Exploring and Analyzing Large-Scale Biological Data Sets

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The Gene Expression Omnibus Database

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GENEVESTIGATOR. Arabidopsis Microarray Database and Analysis Toolbox

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Standardization of sample collection, isolation and analysis methods in extracellular vesicle research

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Genomic analysis of reactive astrogliosis

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The Nuclear-Retained Noncoding RNA MALAT1 Regulates Alternative Splicing by Modulating SR Splicing Factor Phosphorylation

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[9] TM4 Microarray Software Suite

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JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles

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New tools for studying microglia in the mouse and human CNS

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Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data

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Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges

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PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data

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Role of PFKFB3-Driven Glycolysis in Vessel Sprouting

Bock, K. D., Γεωργιάδου, Μ., Schoors, S., Kuchnio, A., Wong, B. W., Cantelmo, A. R., Quaegebeur, A., Ghesquière, B., Cauwenberghs, S., Eelen, G., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.037 · Cited by 1,591

NCBI GEO: mining tens of millions of expression profiles--database and tools update

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The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins

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Challenges of Big Data analysis

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Artificial intelligence to deep learning: machine intelligence approach for drug discovery

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Global reconstruction of the human metabolic network based on genomic and bibliomic data

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Lysosomal calcium signalling regulates autophagy through calcineurin and TFEB

Medina, D. L., Paola, S. D., Peluso, I., Armani, A., Stefani, D. D., Venditti, R., Montefusco, S., Rosato, A. S., Prezioso, C., Forrester, A. R., et al. (2015) · Nature Cell Biology · doi:10.1038/ncb3114 · Cited by 1,452

Genome-Wide Survey of Human Alternative Pre-mRNA Splicing with Exon Junction Microarrays

Johnson, J. M., Castle, J. C., Garrett-Engele, P. W., Kan, Z., Loerch, P., Armour, C. D., Santos, R., Schadt, E. E., Stoughton, R. B., & Shoemaker, D. D. (2003) · Science · doi:10.1126/science.1090100 · Cited by 1,418

Conserved pan-cancer microenvironment subtypes predict response to immunotherapy

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Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

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GMD@CSB.DB: the Golm Metabolome Database

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Enhancement of oxidative and drought tolerance in Arabidopsis by overaccumulation of antioxidant flavonoids

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Transcriptional landscape of the prenatal human brain

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Genomic and transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers

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ChEA3: transcription factor enrichment analysis by orthogonal omics integration

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Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization

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A translational profiling approach for the molecular characterization of CNS cell types

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Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses

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NCBI GEO: mining millions of expression profiles--database and tools

Barrett, T. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki022 · Cited by 1,201

Cell type of origin influences the molecular and functional properties of mouse induced pluripotent stem cells

Polo, J. M., Liu, S. X., Figueroa, M. E., Kulalert, W., Eminli, S., Tan, K. Y., Apostolou, E., Stadtfeld, M., Li, Y., Shioda, T., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1667 · Cited by 1,232

High-Throughput Sequencing of Arabidopsis microRNAs: Evidence for Frequent Birth and Death of MIRNA Genes

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Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice

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Transcriptomics technologies

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Count-based differential expression analysis of RNA sequencing data using R and Bioconductor

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NCBI GEO: archive for functional genomics data sets--10 years on

Barrett, T., Troup, D. B., Wilhite, S. E., Ledoux, P., Evangelista, C., Kim, I. F., Tomashevsky, M., Marshall, K. A., Phillippy, K., Sherman, P. M., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1184 · Cited by 1,127

Database resources of the National Center for Biotechnology

Wheeler, D. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg033 · Cited by 1,124

Plant metabolomics: large-scale phytochemistry in the functional genomics era

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ArrayExpress--a public repository for microarray gene expression data at the EBI

Parkinson, H. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki056 · Cited by 1,077

TNMplot.com: A Web Tool for the Comparison of Gene Expression in Normal, Tumor and Metastatic Tissues

Bartha, Á., & Győrffy, B. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22052622 · Cited by 1,070

Accounting for cellular heterogeneity is critical in epigenome-wide association studies

Jaffe, A. E., & Irizarry, R. A. (2014) · Genome Biology · doi:10.1186/gb-2014-15-2-r31 · Cited by 1,067

NCBI GEO: archive for high-throughput functional genomic data

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Biological Network Exploration with Cytoscape 3

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Multiple common variants for celiac disease influencing immune gene expression

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TFEB controls cellular lipid metabolism through a starvation-induced autoregulatory loop

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Organoids

Zhao, Z., Chen, X., Dowbaj, A. M., Sljukic, A., Bratlie, K., Lin, L., Fong, E. L. S., Balachander, G. M., Chen, Z., Soragni, A., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00174-y · Cited by 1,082

A screen for nuclear transcripts identifies two linked noncoding RNAs associated with SC35 splicing domains

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Distribution of miRNA expression across human tissues

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The Connectivity Map: A new tool for biomedical research

Lamb, J. (2007) · Nature Reviews Cancer · doi:10.1038/nrc2044 · Cited by 945

Deep learning in cancer diagnosis, prognosis and treatment selection

Tran, K. A., Kondrashova, O., Bradley, A., Williams, E. D., Pearson, J. V., & Waddell, N. (2021) · Genome Medicine · doi:10.1186/s13073-021-00968-x · Cited by 932

A subtype of childhood acute lymphoblastic leukaemia with poor treatment outcome: a genome-wide classification study

den Boer, M. L., van Slegtenhorst, M., de Menezes, R. X., Cheok, M. H.-C., Buijs-Gladdines, J. G. C. A. M., Peters, S. T. C. J. M., van Zutven, L. J. C. M., Beverloo, H. B., van der Spek, P. J., Escherich, G., et al. (2009) · The Lancet Oncology · doi:10.1016/s1470-2045(08)70339-5 · Cited by 927

The Arabidopsis NFYA5 Transcription Factor Is Regulated Transcriptionally and Posttranscriptionally to Promote Drought Resistance

Li, W., Oono, Y., Zhu, J., He, X., Wu, J., Iida, K., Lu, X., Cui, X., Jin, H., & Zhu, J. (2008) · The Plant Cell · doi:10.1105/tpc.108.059444 · Cited by 917

Sharing Detailed Research Data Is Associated with Increased Citation Rate

Piwowar, H. A., Day, R. S., & Fridsma, D. B. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000308 · Cited by 881

PREDICT: a method for inferring novel drug indications with application to personalized medicine

Gottlieb, A., Stein, G. Y., Ruppin, E., & Sharan, R. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.26 · Cited by 900

c-Jun overexpression in CAR T cells induces exhaustion resistance

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Swarm Learning for decentralized and confidential clinical machine learning

Warnat-Herresthal, S., Schultze, H., Shastry, K. L., Manamohan, S., Mukherjee, S., Garg, V., Sarveswara, R., Händler, K., Pickkers, P., Aziz, N. A., et al. (2021) · Nature · doi:10.1038/s41586-021-03583-3 · Cited by 884

Ten Simple Rules for Reproducible Computational Research

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In Vivo Imaging Reveals Extracellular Vesicle-Mediated Phenocopying of Metastatic Behavior

Zomer, A., Maynard, C., Verweij, F. J., Kamermans, A., Schäfer, R., Beerling, E., Schiffelers, R. M., de Wit, E., Berenguer, J., Ellenbroek, S. I. J., et al. (2015) · Cell · doi:10.1016/j.cell.2015.04.042 · Cited by 893

Gateways to the FANTOM5 promoter level mammalian expression atlas

Lizio, M., Harshbarger, J., Shimoji, H., Severin, J., Kasukawa, T., Sahin, S., Abugessaisa, I., Fukuda, S., Hori, F., Ishikawa-Kato, S., et al. (2015) · Genome Biology · doi:10.1186/s13059-014-0560-6 · Cited by 871

High-Resolution Temporal Profiling of Transcripts during Arabidopsis Leaf Senescence Reveals a Distinct Chronology of Processes and Regulation

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DNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia

Figueroa, M. E., Lugthart, S., Li, Y., Erpelinck-Verschueren, C. A. J., Deng, X., Christos, P. J., Schifano, E. D., Booth, J. G., van Putten, W., Skrabanek, L. A., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2009.11.020 · Cited by 849

Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain

Gibbs, J. R., van der Brug, M. P., Hernandez, D. G., Traynor, B. J., Nalls, M. A., Lai, S.-L., Arepalli, S., Dillman, A., Rafferty, I. P., Troncoso, J., et al. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000952 · Cited by 769

Coexpression Analysis of Human Genes Across Many Microarray Data Sets

Lee, H. K., Hsu, A. K., Sajdak, J., Qin, J., & Pavlidis, P. (2004) · Genome Research · doi:10.1101/gr.1910904 · Cited by 770

Circulating Tumor Cell Clustering Shapes DNA Methylation to Enable Metastasis Seeding

Gkountela, S., Castro-Giner, F., Szczerba, B. M., Vetter, M. H. F., Landin, J., Scherrer, R., Krol, I., Scheidmann, M. C., Beisel, C., Stirnimann, C. U., et al. (2019) · Cell · doi:10.1016/j.cell.2018.11.046 · Cited by 822

Discovery and Preclinical Validation of Drug Indications Using Compendia of Public Gene Expression Data

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