KnockTF: a comprehensive human gene expression profile database with knockdown/knockout of transcription factors

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625

limma powers differential expression analyses for RNA-sequencing and microarray studies

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BEDTools: a flexible suite of utilities for comparing genomic features

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Multiplex Genome Engineering Using CRISPR/Cas Systems

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NCBI GEO: archive for functional genomics data sets—update

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Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells

Elbashir, S. M., Harborth, J., Lendeckel, W., Yalcin, A., Weber, K., & Tuschl, T. (2001) · Nature · doi:10.1038/35078107 · Cited by 9,456

KEGG: new perspectives on genomes, pathways, diseases and drugs

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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950

The MEME Suite

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Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage

Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A., & Liu, D. R. (2016) · Nature · doi:10.1038/nature17946 · Cited by 5,437

Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities

Müller‐Dott, S., Tsirvouli, E., Vázquez, M., Flores, R. O. R., Badia-i-Mompel, P., Fallegger, R., Türei, D., Lægreid, A., & Sáez-Rodríguez, J. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad841 · Cited by 425

Transcription factors: Bridge between cell signaling and gene regulation

Weidemüller, P., Kholmatov, M. M., Petsalaki, E., & Zaugg, J. B. (2021) · PROTEOMICS · doi:10.1002/pmic.202000034 · Cited by 295

GTRD: an integrated view of transcription regulation

Kolmykov, S. K., Yevshin, I., Kulyashov, M. A., Sharipov, R., Kondrakhin, Y. V., Makeev, V. J., Kulakovskiy, I. V., Kel, A. E., & Kolpakov, F. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1057 · Cited by 286

MultiNicheNet: a flexible framework for differential cell-cell communication analysis from multi-sample multi-condition single-cell transcriptomics dataPreprint

Browaeys, R., Gilis, J., Sang-aram, C., Bleser, P. D., Hoste, L., Tavernier, S. J., Lambrechts, D., Seurinck, R., & Saeys, Y. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.13.544751 · Cited by 136

Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data

Yuan, Q., & Duren, Z. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02182-7 · Cited by 118

Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics

Wang, L., Trasanidis, N., Wu, T., Dong, G., Hu, M., Bauer, D. E., & Pinello, L. (2023) · Nature Methods · doi:10.1038/s41592-023-01971-3 · Cited by 122

SEdb 2.0: a comprehensive super-enhancer database of human and mouse

Wang, Y., Song, C., Zhao, J., Zhang, Y., Zhao, X., Feng, C., Zhang, G., Zhu, J., Wang, F., Qian, F., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac968 · Cited by 111

Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications

Su, M., Pan, T., Chen, Q.-Z., Zhou, W., Gong, Y., Xu, G., Yan, H.-Y., Li, S., Shi, Q.-Z., Zhang, Y., et al. (2022) · Military Medical Research · doi:10.1186/s40779-022-00434-8 · Cited by 114

TFTF: An R-Based Integrative Tool for Decoding Human Transcription Factor–Target Interactions

Wang, J. (2024) · Biomolecules · doi:10.3390/biom14070749 · Cited by 78

The 27th annual Nucleic Acids Research database issue and molecular biology database collection

Rigden, D. J., & Fernández, X. M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1161 · Cited by 74

Targeting the immune privilege of tumor-initiating cells to enhance cancer immunotherapy

Yang, C. G., Geng, H., Yang, X., Ji, S., Liu, Z., Feng, H., Li, Q., Zhang, T., Zhang, S., Ma, X., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.10.008 · Cited by 75

TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data

Zhang, G., Song, C., Yin, M., Liu, L., Zhang, Y., Li, Y., Zhang, J., Guo, M., & Li, C. (2025) · Nature Communications · doi:10.1038/s41467-025-58921-0 · Cited by 55

KnockTF 2.0: a comprehensive gene expression profile database with knockdown/knockout of transcription (co-)factors in multiple species

Feng, C., Song, C., Song, S., Zhang, G., Yin, M., Zhang, Y., Qian, F., Wang, Q., Guo, M., & Li, C. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1016 · Cited by 53

GPSAdb: a comprehensive web resource for interactive exploration of genetic perturbation RNA-seq datasets

Guo, S., Xu, Z.-G., Dong, X., Hu, D., Jiang, Y., Wang, Q., Zhang, J., Zhou, Q., Liu, S., & Song, W. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1066 · Cited by 43

MYCN Drives a Tumor Immunosuppressive Environment Which Impacts Survival in Neuroblastoma

Raieli, S., Renzo, D. D., Lampis, S., Amadesi, C., Montemurro, L., Pession, A., Hrelia, P., Fischer, M., & Tonelli, R. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.625207 · Cited by 45

Characterization of super‐enhancer‐associated functional lncRNAs acting as ceRNAs in ESCC

Wang, Q., Liu, P., Chen, Y., Liao, L., Chen, J., Li, M., Li, Y., Qian, F., Zhang, Y., Wang, F., et al. (2020) · Molecular Oncology · doi:10.1002/1878-0261.12726 · Cited by 41

eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse

Song, C., Zhang, G., Mu, X., Feng, C., Zhang, Q., Song, S., Zhang, Y., Yin, M., Zhang, H., Tang, H., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad925 · Cited by 40

IReNA: Integrated Regulatory Network Analysis of Single-Cell Transcriptomes and Chromatin Accessibility Profiles

Jiang, J., Lyu, P., Li, J., Huang, S., Tao, J., Blackshaw, S., Qian, J. X., & Wang, J. (2022) · iScience · doi:10.1016/j.isci.2022.105359 · Cited by 40

Nonparametric single-cell multiomic characterization of trio relationships between transcription factors, target genes, and cis-regulatory regions

Jiang, Y., Harigaya, Y., Zhang, Z., Zhang, H., Zang, C., & Zhang, N. R. (2022) · Cell Systems · doi:10.1016/j.cels.2022.08.004 · Cited by 41

Discovery of Targets for Immune–Metabolic Antitumor Drugs Identifies Estrogen-Related Receptor Alpha

Sahu, A. D., Wang, X., Munson, P. B., Klomp, J. P. G., Wang, X., Gu, S. S., Qian, G., Nicol, P., Zeng, Z., Wang, C., et al. (2023) · Cancer Discovery · doi:10.1158/2159-8290.cd-22-0244 · Cited by 35

Chronic Stress‐Induced and Tumor Derived SP1 + Exosomes Polarizing IL‐1β + Neutrophils to Increase Lung Metastasis of Breast Cancer

Zhang, L., Pan, J., Wang, M., Yang, J., Zhu, S., Li, L., Hu, X., Wang, Z., Pang, L., Li, P., et al. (2024) · Advanced Science · doi:10.1002/advs.202310266 · Cited by 39

LncSEA 2.0: an updated platform for long non-coding RNA related sets and enrichment analysis

Zhang, G., Song, C., Fan, S., Yin, M., Wang, X., Zhang, Y., Huang, X., Li, Y., Shang, D., Li, C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1008 · Cited by 30

ADRB1 was identified as a potential biomarker for breast cancer by the co-analysis of tumor mutational burden and immune infiltration

Wang, J., Zhang, X., Li, J., Ma, X., Feng, F., Liu, L., Wu, J., & Sun, C. (2020) · Aging · doi:10.18632/aging.104204 · Cited by 29

scGRN: a comprehensive single-cell gene regulatory network platform of human and mouse

Huang, X., Song, C., Zhang, G., Li, Y., Zhao, Y., Zhang, Q., Zhang, Y., Fan, S., Zhao, J., Xie, L., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad885 · Cited by 29

Computational tools for inferring transcription factor activity

Hecker, D., Lauber, M., Ardakani, F. B., Ashrafiyan, S., Manz, Q., Kersting, J., Hoffmann, M., Schulz, M. H., & List, M. (2023) · PROTEOMICS · doi:10.1002/pmic.202200462 · Cited by 27

BARTweb: a web server for transcriptional regulator association analysis

Ma, W., Wang, Z., Zhang, Y., Magee, N. E., Feng, Y., Shi, R., Chen, Y., & Zang, C. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab022 · Cited by 25

The Landscape of m6A Regulators in Multiple Brain Regions of Alzheimer’s Disease

Liu, Z., Xia, Q. H., Zhao, X. L., Zheng, F., Xiao, J., Ge, F., Wang, D., & Gao, X. (2023) · Molecular Neurobiology · doi:10.1007/s12035-023-03409-5 · Cited by 25

Superenhancers as master gene regulators and novel therapeutic targets in brain tumors

Zhuang, H.-H., Qu, Q., Teng, X.-Q., Dai, Y.-H., & Qu, J. (2023) · Experimental & Molecular Medicine · doi:10.1038/s12276-023-00934-0 · Cited by 24

OUP accepted manuscript

Xu, M., Bai, X., Ai, B., Zhang, G., Song, C., Zhao, J., Wang, Y., Wei, L., Qian, F., Li, Y., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab1114 · Cited by 22

Prior vaccination prevents overactivation of innate immune responses during COVID-19 breakthrough infection

Chan, L., Pinedo, K., Stabile, M. A., Hamlin, R. E., Pienkos, S. M., Ratnasiri, K., Biobank, S. C.-1., Yang, S. S., Blomkalns, A. L., Nadeau, K. C., et al. (2025) · Science Translational Medicine · doi:10.1126/scitranslmed.adq1086 · Cited by 22

Pan-Cancer Analysis of Prognostic and Immune Infiltrates for CXCs

Long, L., Yao, W., Yan, S. R., Dong, X., Lv, Z., Jing, Q., Wang, Q., Ma, B., Hao, C., Xue, D., et al. (2021) · Cancers · doi:10.3390/cancers13164153 · Cited by 19

RNA-seq analysis and in vivo experiments identified the protective effect of kaempferol on idiopathic pulmonary fibrosis by regulating the PPARG/TNC signaling pathway to reduce ECM deposition

Zhang, X., Xie, Y., Cai, Y., Huang, H.-T., Liang, H., Liao, G., Jiang, Y., Peng, X., Zhan, S., & Huang, X. (2024) · Food & Function · doi:10.1039/d4fo01474j · Cited by 18

High dose isoleucine stabilizes nuclear PTEN to suppress the proliferation of lung cancer

Wang, H., Chen, S., Kang, W., Ding, B., Cui, S., Zhou, L., Zhang, N., Luo, H., Wang, M., Zhang, F., et al. (2023) · Discover Oncology · doi:10.1007/s12672-023-00634-1 · Cited by 18

Super-enhancer omics in stem cell

Ma, H., Qu, J., Pang, Z., Luo, J., Yan, M., Xu, W.-X., Zhuang, H., Liu, L., & Qu, Q. (2024) · Molecular Cancer · doi:10.1186/s12943-024-02066-z · Cited by 23

Reconstruction of tissue-specific genome-scale metabolic models for human cancer stem cells

Barata, T., Vieira, V., Rodrigues, R., das Neves, R. P., & Rocha, M. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.105177 · Cited by 15

TREAT: Therapeutic RNAs exploration inspired by artificial intelligence technology

Luo, Y., Liu, L., He, Z., Zhang, S., Huo, P., Wang, Z., Jiaxin, Q., Zhao, L., Wu, Y., Zhang, D., et al. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.10.011 · Cited by 14

A Functional Network Model of the Metastasis Suppressor PEBP1/RKIP and Its Regulators in Breast Cancer Cells

Ahmed, M., Lai, T. H., Kim, W., & Kim, D. R. (2021) · Cancers · doi:10.3390/cancers13236098 · Cited by 14

Epiregulon: Single-cell transcription factor activity inference to predict drug response and drivers of cell states

Włodarczyk, T., Lun, A. T. L., Wu, D. H., Shi, M., Ye, X., Menon, S., Toneyan, S., Seidel, K., Wang, L., Tan, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-62252-5 · Cited by 18

Drug screening and biomarker gene investigation in cancer therapy through the human transcriptional regulatory network

He, Z., Gao, K., Dong, L., Liu, L., Qu, X., Zou, Z., Wu, Y., Bu, D., Guo, J., & Zhao, Y. C. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.02.005 · Cited by 13

Ferroptosis inhibitors reduce celastrol toxicity and preserve its insulin sensitizing effects in insulin resistant HepG2 cells

Liu, J., Zhang, X., Cai, B.-L., Qi, M.-M., Chi, Y.-B., Peng, B., & Zhang, D. (2024) · Journal of Chinese Integrative Medicine · doi:10.1016/j.joim.2024.03.007 · Cited by 13

TFTG: A comprehensive database for human transcription factors and their targets

Zhou, X., Zhou, L., Qian, F., Chen, J., Zhang, Y., Yu, Z., Zhang, J., Yang, Y., Li, Y., Song, C., et al. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.04.036 · Cited by 13

TRIB3 mediates vascular calcification by facilitating self-ubiquitination and dissociation of Smurf1 in chronic kidney disease

Li, Y., Ma, C., Sheng, Y., Huang, S., Sun, H., Ti, Y., Wang, Z., Wang, F., Chen, F., Chen, L., et al. (2025) · Journal of Clinical Investigation · doi:10.1172/jci175972 · Cited by 13

CRdb: a comprehensive resource for deciphering chromatin regulators in human

Zhang, Y., Zhang, Y., Song, C., Zhao, X., Ai, B., Wang, Y., Zhou, L., Zhu, J., Feng, C., Xu, L., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac960 · Cited by 11

Integrating binding and expression data to predict transcription factors combined function

Ahmed, M., Min, D. S., & Kim, D. R. (2020) · BMC Genomics · doi:10.1186/s12864-020-06977-1 · Cited by 12

The feedback loop of EFTUD2/c-MYC impedes chemotherapeutic efficacy by enhancing EFTUD2 transcription and stabilizing c-MYC protein in colorectal cancer

Zhu, X., Li, C., Gao, Y., Zhang, Q., Wang, T., Zhou, H., Bu, F., Chen, J., Mao, X., He, Y., et al. (2024) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-023-02873-0 · Cited by 11

Broad misappropriation of developmental splicing profile by cancer in multiple organs

Singh, A., Rajeevan, A., Gopalan, V., Agrawal, P., Day, C., & Hannenhalli, S. S. (2022) · Nature Communications · doi:10.1038/s41467-022-35322-1 · Cited by 9

ADGRE5-centered Tsurv model in T cells recognizes responders to neoadjuvant cancer immunotherapy

Li, J., Meng, Z., Cao, Z., Lü, W., Yang, Y., Li, Z., & Lü, S. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1304183 · Cited by 11

PerturbDB for unraveling gene functions and regulatory networks

Yang, B., Zhang, M., Shi, Y., Zheng, B.-Q., Shi, C., Lu, D., Yang, Z.-Z., Dong, Y.-M., Zhu, L., Ma, X., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae777 · Cited by 12

TRAF1 promotes the progression of Helicobacter pylori-associated gastric cancer through EGFR/STAT/OAS signalling

Zhang, M., Yuan, L., Yang, X., Zhao, X., Xie, J., Liu, X., & Wang, F. W. (2025) · Life Sciences · doi:10.1016/j.lfs.2025.123656 · Cited by 10

Reviewing the Developing Significance of the Serine Protease PRSS23

Schulten, H.-J. (2025) · Frontiers in Bioscience-Landmark · doi:10.31083/fbl27294 · Cited by 9

Analysis of single-cell RNA sequencing in human oocytes with diminished ovarian reserve uncovers mitochondrial dysregulation and translation deficiency

Li, X., Wu, X., Zhang, H., Liu, P., Xia, L., Zhang, N., Tian, L., Li, Z., Lu, J., Zhao, Y., et al. (2024) · Reproductive Biology and Endocrinology · doi:10.1186/s12958-024-01321-8 · Cited by 9

Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs

Minaeva, M., Domingo, J., Rentzsch, P., & Lappalainen, T. (2024) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqae178 · Cited by 9

GREAP: a comprehensive enrichment analysis software for human genomic regions

Yang, Y., Qian, F., Li, X., Li, Y., Zhou, L., Wang, Q., Zhou, X., Zhang, J., Song, C., Yu, Z., et al. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac329 · Cited by 9

Targeting the HLA-E–NKG2A axis in combination with MS-275 enhances NK cell-based immunotherapy against DMG

Deng, Y., Liu, J., Pu, Z., Wang, Y., Li, T., Jiang, Z., Xie, L. Z., Zhang, X., Chen, Y., Yang, M., et al. (2025) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-025-03390-y · Cited by 8

Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods

Karamveer, K., & Uzun, Y. (2024) · Bioinformatics and Biology Insights · doi:10.1177/11779322241287120 · Cited by 9

Epigenetic control of metabolic identity across cell types

Pacheco, M. P., Gérard, D., Mangan, R. J., Chapman, A. R., Hecker, D., Kellis, M., Schulz, M. H., Sinkkonen, L., & Sauter, T. (2025) · BMC Genomics · doi:10.1186/s12864-025-12155-y · Cited by 7

Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia

Zhong, Y., Zhao, J. F., Deng, H., Wu, Y., Li, Z., Yang, M., Liu, Q., Luo, G., Ma, W., & Li, H. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1088261 · Cited by 7

Systematic discovery of transcription factors that improve hPSC-derived cardiomyocyte maturation via temporal analysis of bioengineered cardiac tissues

Kumar, A., He, S., & Mali, P. (2023) · APL Bioengineering · doi:10.1063/5.0137458 · Cited by 8

Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets

Lu, Z., Xiao, X., Zheng, Q., Wang, X., & Xu, L. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae366 · Cited by 7

Integrative Epigenomic Analysis of Transcriptional Regulation of Human CircRNAs

Li, X., Tang, Z., Peng, L., Li, Y., Qian, F., Zhao, J., Ding, L., Du, X., Li, M., Zhang, J., et al. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2020.590672 · Cited by 7

CohesinDB: a comprehensive database for decoding cohesin-related epigenomes, 3D genomes and transcriptomes in human cells

Wang, J., & Nakato, R. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac795 · Cited by 7

Enigma of AMP-activated protein kinase subunit expression in glioma

Dongre, S., Soni, N., Chaudhary, M., Prakasan, A., Sharma, A., & Bissa, B. (2025) · Academia oncology. · doi:10.20935/acadonco7881 · Cited by 6

Evolutionary innovation within conserved gene regulatory networks underlying biomineralized skeletons in Bilateria

Bai, Y., Min, Y., Liu, S., Hu, Y., Jin, S., Yu, H., Kong, L., Macqueen, D. J., Du, S., & Li, Q. (2026) · Molecular Biology and Evolution · doi:10.1093/molbev/msag019 · Cited by 6

Circular RNA CircSLC22A23 Promotes Gastric Cancer Progression by Activating HNRNPU Expression

Wu, X., Cao, C., Li, Z., Xie, Y., Zhang, S., Sun, W., & Guo, J. (2024) · Digestive Diseases and Sciences · doi:10.1007/s10620-024-08291-2 · Cited by 6

Experiment level curation of transcriptional regulatory interactions in neurodevelopment

Chu, E. C.-P., Morin, A. M., Chang, T. H. C., Nguyen, T. G., Tsai, Y.-C., Sharma, A., Liu, C. C., & Pavlidis, P. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009484 · Cited by 6

Identification of Transcription Factors Regulating SARS-CoV-2 Tropism Factor Expression by Inferring Cell-Type-Specific Transcriptional Regulatory Networks in Human Lungs

Tong, H., Chen, H., & Williams, C. (2022) · Viruses · doi:10.3390/v14040837 · Cited by 6

Identification and Validation of Autophagy-Related Genes in Primary Ovarian Insufficiency by Gene Expression Profile and Bioinformatic Analysis

Lv, S., Sun, J., & Sun, J. (2022) · Analytical Cellular Pathology · doi:10.1155/2022/9042380 · Cited by 6

Identification of TUBB4A as a Prognostic Biomarker of Melanoma by Transcriptomic Data and In Vitro Experiments

Zhang, J., Li, Z., Liu, J., Wu, Q., Yun, Y., Cao, Y., Gao, W., Luo, J., & Liu, X. (2023) · Technology in Cancer Research & Treatment · doi:10.1177/15330338231184842 · Cited by 6

Identification of Autophagy-Related Targets of Berberine against Non-Small Cell Lung Cancer and Their Correlation with Immune Cell Infiltration By Combining Network Pharmacology, Molecular Docking, and Experimental Verification

Xu, L. Z. (2023) · Critical Reviews in Immunology · doi:10.1615/critrevimmunol.2023049923 · Cited by 6

BART Cancer: a web resource for transcriptional regulators in cancer genomes

Thomas, Z. V., Wang, Z., & Zang, C. (2021) · NAR Cancer · doi:10.1093/narcan/zcab011 · Cited by 6

Identification and validation of pyroptosis-related genes in Alzheimer’s disease based on multi-transcriptome and machine learning

Wang, Y., Li, Y., Zhou, L., Yuan, Y., Liu, C., Zeng, Z., Chen, Y., He, Q., & Wu, Z. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2025.1568337 · Cited by 5

Identification of the EBF1/ETS2/KLF2-miR-126-Gene Feed-Forward Loop in Breast Carcinogenesis and Stemness

Gambacurta, A., Tullio, V., Savini, I., Mauriello, A., Catani, M. V., & Gasperi, V. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26010328 · Cited by 5

MYC promotes group 3 medulloblastoma cell proliferation and alleviates ROS-induced cell death by upregulating transketolase

Wang, S., Zhang, D., Wang, C., & Liu, Y. (2025) · Acta Neuropathologica Communications · doi:10.1186/s40478-025-02051-7 · Cited by 5

HAS2 facilitates glioma cell malignancy and suppresses ferroptosis in an FZD7 ‐dependent manner

Liu, Z., Yu, K., Chen, K., Liu, J.-L., Dai, K., & Zhao, P. (2024) · Cancer Science · doi:10.1111/cas.16232 · Cited by 5

Comprehensive Analyses of the Expression, Genetic Alteration, Prognosis Significance, and Interaction Networks of m6A Regulators Across Human Cancers

Shi, X., Zhang, J., Jiang, Y., Zhang, C., Luo, X., Wu, J., & Li, J. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.771853 · Cited by 5

Comparative gene regulatory network analysis in Alzheimer’s disease and major depressive disorder identifies shared core regulatory circuitsPreprint

Puype, H., Deschildre, J., & Vermeirssen, V. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.23.529626 · Cited by 4

Decoding LINC00052 role in breast cancer by bioinformatic and experimental analyses

Sánchez-López, J. M., Juarez-Mancera, M. A., Bustamante, B., Ruiz-Silvestre, A., Espinosa, M., Mendoza‐Almanza, G., Ceballos‐Cancino, G., Meléndez-Zajgla, J., Maldonado, V., & Lizárraga, F. (2024) · RNA Biology · doi:10.1080/15476286.2024.2355393 · Cited by 4

Mechanistic analysis of enhancer sequences in the estrogen receptor transcriptional program

Tabe-Bordbar, S., Song, Y. J., Lunt, B., Alavi, Z., Prasanth, K. V., & Sinha, S. (2024) · Communications Biology · doi:10.1038/s42003-024-06400-5 · Cited by 5

Maximizing the utility of public data

吉村, 克., Kim, H. J., & Kim, D. R. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1106631 · Cited by 4

PertOrg 1.0: a comprehensive resource of multilevel alterations induced in model organisms by in vivo genetic perturbation

Zhai, Z., Zhang, X., Zhou, L., Lin, Z., Kuang, N., Li, Q., Ma, Q., Tao, H., Gao, J., Ma, S., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac872 · Cited by 4

Cis-Cardio: A comprehensive analysis platform for cardiovascular-relavant cis-regulation in human and mouse

Song, C., Zhang, Y., Huang, H. W., Wang, Y., Zhao, X., Zhang, G., Yin, M., Feng, C., Wang, Q., Qian, F., et al. (2023) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2023.07.030 · Cited by 4

Characterizing the targets of transcription regulators by aggregating ChIP-seq and perturbation expression data setsPreprint

Morin, A. M., Chu, E. C.-P., Sharma, A., Adrian-Hamazaki, A., & Pavlidis, P. (2023) · Genome Research · doi:10.1101/gr.277273.122 · Cited by 4

Dissecting the functions and regulatory mechanisms of disulfidoptosis-related RPN1 in pan-cancer: modulation of immune microenvironment and cellular senescence

Qin, L., Liang, T., Zhang, H., Gong, X., Wei, M., Song, X., Hu, Y., Zhu, X., Hu, W., Li, J., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1512445 · Cited by 4

Unmeasured human transcription factor ChIP-seq data shape functional genomics and demand strategic prioritization

Tahara, S., & Ozaki, H. (2025) · Briefings in Functional Genomics · doi:10.1093/bfgp/elaf016 · Cited by 3

C/EBPβ-induced alternative splicing of RCAN1 generates a potent TCR-T target in mesenchymal glioblastoma

Xiong, Z., Kong, Q., Chagantipati, B., Stepniak, A. L., Jaswal, A. P., Sneiderman, C. T., Han, Y., Jackson, S. A., Raphael, R. A., Zhang, W., et al. (2025) · Cellular and Molecular Immunology · doi:10.1038/s41423-025-01360-0 · Cited by 3

Multi-omics mapping identifies CYBA-mediated mitochondrial dysfunction driving macrophage polarization and ferroptosis via Nrf2 pathway in atherosclerosis

Dong, C. X., Shen, R., Pan, C., Zhang, J., Yu, K., & Zeng, Q. (2026) · APL Bioengineering · doi:10.1063/5.0303714 · Cited by 3

NFAT activation by FKBP52 promotes cancer cell proliferation by suppressing p53

Hanaki, S., Habara, M., Tomiyasu, H., Sato, Y., Miki, Y., Masaki, T., Shibutani, S., & Shimada, M. (2024) · Life Science Alliance · doi:10.26508/lsa.202302426 · Cited by 3

Analysis in silico of the functional interaction between WNT5A and YAP/TEAD signaling in cancer

Astudillo, P. (2021) · PeerJ · doi:10.7717/peerj.10869 · Cited by 3

STARNet enables spatially resolved inference of gene regulatory networks from spatial multi-omics dataPreprint

Hu, L., Zhang, S., Zhang, X., Luo, Y., Gu, H., Liu, P., Mao, S., Chen, L., Xia, Y., Yang, M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.21.671434 · Cited by 3

Transcription factor occupancy limits DNA methylation and determines ICAM1 expression in breast cancer

Chen, M., Zhou, Y., Fu, Z., & Wu, C. (2024) · Acta Biochimica et Biophysica Sinica · doi:10.3724/abbs.2024237 · Cited by 2

Integrating bulk and single-cell transcriptome profiling to uncover diagnostic biomarkers and regulatory mechanisms of oxidative stress in spinal cord injury

Li, J., Tong, K., Zhou, J., Li, S., He, Z., Wang, F., Chen, H., Li, H., Cheng, G., Li, J., et al. (2025) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-24-00693 · Cited by 3

Localization of Noise in Biochemical Networks

Fajiculay, E., & Hsu, C. (2023) · ACS Omega · doi:10.1021/acsomega.2c06113 · Cited by 2

Identifying CD1c as a potential biomarker by the comprehensive exploration of tumor mutational burden and immune infiltration in diffuse large B cell lymphoma

Xiang, X., Gao, L., Zhang, Y., Zhu, Q., Zhao, S., Liu, W., Ye, Y., Tang, Y., & Zhang, W. (2023) · PeerJ · doi:10.7717/peerj.16618 · Cited by 2

Disulfidptosis-related long non-coding RNAs predict prognosis and indicate therapeutic response in non-small cell lung carcinoma

Liu, H., He, S., Tan, L., Li, M., Chen, C., & Tan, R. (2024) · ONCOLOGIE · doi:10.1515/oncologie-2023-0384 · Cited by 2

TSCRE: a comprehensive database for tumor-specific cis-regulatory elements

Peng, G., Liu, B., Zheng, M., Zhang, L., Li, H., Liu, M., Liang, Y., Chen, T., Luo, X., Shi, X., et al. (2024) · NAR Cancer · doi:10.1093/narcan/zcad063 · Cited by 2

BARTweb: a web server for transcription factor association analysisPreprint

Ma, W., Wang, Z., Zhang, Y., Magee, N. E., Chen, Y., & Zang, C. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.17.952838 · Cited by 2

Deciphering FOXM1 regulation: implications for stemness and metabolic adaptations in glioblastoma

Swati, K., Arfin, S., Agrawal, K., Jha, S. K., Rajendran, R. L., Prakash, A., Kumar, D., Gangadaran, P., & Ahn, B. (2025) · Medical Oncology · doi:10.1007/s12032-025-02639-y · Cited by 1

NFATC3 enhances osteosarcoma progression by increasing PD-L1 and CXCL2 levels

Liang, F., Tang, B., Chen, C., Meng, G., Huang, N., Xiang, J., Jian, H., Huang, Z., & Cheng, J. (2025) · Medical Oncology · doi:10.1007/s12032-025-02850-x · Cited by 1

Targeting MTPN sensitizes pancreatic cancer of wild-type BRCA1/2 to Cisplatin-based chemotherapy

Wang, Z., Huang, X., Bai, T., Jin, Y., Gong, T., Wu, W., Bielike, K., Wang, Q., & Wang, L. (2025) · Cancer Gene Therapy · doi:10.1038/s41417-025-00925-5 · Cited by 1

The LMO2-LDB1-TAL1 complex regulates transcription networks in acute myeloid leukemia

Dunham, N. R., Wang, Z., Neelamraju, Y., Guo, Y., Paudel, B. B., Meydan, C., Gandara, J. A., Abdelmalak, F., Fan, H., Hardwick, J. A., et al. (2025) · Blood Neoplasia · doi:10.1016/j.bneo.2025.100186 · Cited by 1

KnockTF 2.0: a comprehensive gene expression profile database with knockdown/knockout of transcription (co-)factors in multiple species

Feng, C., Song, C., Song, S., Zhang, G., Yin, M., Zhang, Y., Qian, F., Wang, Q., Guo, M., & Li, C. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1016 · Cited by 53

TFTG: A comprehensive database for human transcription factors and their targets

Zhou, X., Zhou, L., Qian, F., Chen, J., Zhang, Y., Yu, Z., Zhang, J., Yang, Y., Li, Y., Song, C., et al. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.04.036 · Cited by 13

Identifying biologically interpretable transcription factor knockout targets by jointly analyzing the transcription factor knockout microarray and the ChIP-chip data

Yang, T.-H., & Wu, W. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-102 · Cited by 27

Systematic target function annotation of human transcription factors

Li, Y. F., & Altman, R. B. (2018) · BMC Biology · doi:10.1186/s12915-017-0469-0 · Cited by 18

The Functional Consequences of Variation in Transcription Factor Binding

Cusanovich, D. A., Pavlovic, B. J., Pritchard, J. K., & Gilad, Y. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004226 · Cited by 209