Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders

Mendelian Inheritance in Man: A Catalog of Human Genes and Genetic Disorders

McKusick, V. A. (1998) · DigitalGeorgetown (Georgetown University Library) · Cited by 681

ChickVD: a sequence variation database for the chicken genome

Wang, J. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki092 · Cited by 41

Distribution and Effects of Nonsense Polymorphisms in Human Genes

Yamaguchi‐Kabata, Y., Shimada, M. K., Hayakawa, Y., Minoshima, S., Chakraborty, R., Gojobori, T., & Imanishi, T. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003393 · Cited by 44

Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods

Notaro, M., Schubach, M., Robinson, P. N., & Valentini, G. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1854-y · Cited by 41

In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine

Wu, Q., Cai, C., Guo, P., Chen, M., Wu, X., Zhou, J., Luo, Y., Zou, Y., Liu, A., Wang, Q., et al. (2019) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.00458 · Cited by 40

High expression of DNA damage-inducible transcript 4 (DDIT4) is associated with advanced pathological features in the patients with colorectal cancer

Fattahi, F., Zanjani, L. S., Shams, Z. H., Kiani, J., Mehrazma, M., Najafi, M., & Madjd, Z. (2021) · Scientific Reports · doi:10.1038/s41598-021-92720-z · Cited by 41

Searching Online Mendelian Inheritance in Man ( OMIM ) for Information for Genetic Loci Involved in Human Disease

Baxevanis, A. D. (2002) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0102s00 · Cited by 39

Nevoid basal cell carcinoma syndrome: a review of the literature and a report of a case

Bakaeen, G., Rajab, L. D., Sawair, F., Hamdan, M. A., & DALLAL, N. D. (2004) · International Journal of Paediatric Dentistry · doi:10.1111/j.1365-263x.2004.00560.x · Cited by 39

ProSplicer: a database of putative alternative splicing information derived from protein, mRNA and expressed sequence tag sequence data

Huang, H., Horng, J., Lee, C.-C., & Liu, B.-J. (2003) · Genome biology · doi:10.1186/gb-2003-4-4-r29 · Cited by 39

Meta-analysis of heterogeneous data sources for genome-scale identification of risk genes in complex phenotypes

Pers, T. H., Hansen, N. T., Lage, K., Koefoed, P., Dworzyński, P., Miller, M. L., Flint, T. J., Mellerup, E. T., Dam, H., Andreassen, O. A., et al. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20580 · Cited by 38

Integrating node embeddings and biological annotations for genes to predict disease-gene associations

Ata, S. K., Ou-Yang, L., Fang, Y., Kwoh, C.-K., Wu, M., & Li, X. (2018) · BMC Systems Biology · doi:10.1186/s12918-018-0662-y · Cited by 38

Novel Perspective: Focusing on the X Chromosome in Reproductive Cancers

Liao, D. J., Du, Q.-Q., Yu, B. W., Grignon, D. J., & Sarkar, F. H. (2003) · Cancer Investigation · doi:10.1081/cnv-120022385 · Cited by 38

Genetics of Cerebrovascular Disorders

Meschia, J. F., Brott, T. G., & Brown, R. D. (2005) · Mayo Clinic Proceedings · doi:10.1016/s0025-6196(11)62969-8 · Cited by 38

Integrative analysis of human protein, function and disease networks

Liu, W., Wu, A., Pellegrini, M. A., & Wang, X. (2015) · Scientific Reports · doi:10.1038/srep14344 · Cited by 37

Identification of genes and miRNA associated with idiopathic recurrent pregnancy loss: an exploratory data mining study

Bahia, W., Soltani, I., Abidi, A., Haddad, A., Ferchichi, S., Menif, S., & Almawi, W. Y. (2020) · BMC Medical Genomics · doi:10.1186/s12920-020-00730-z · Cited by 37

Design of Genetics Home Reference: A New NLM Consumer Health Resource

Mitchell, J. A., Fun, J., & McCray, A. T. (2004) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1549 · Cited by 37

Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies

Teber, E., Liu, J. Y., Ballouz, S., Fatkin, D., & Wouters, M. A. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-s1-s69 · Cited by 36

Informatics in Radiology: Radiology Gamuts Ontology: Differential Diagnosis for the Semantic Web

Budovec, J. J., Lam, C. A., & Kahn, C. E. (2013) · Radiographics · doi:10.1148/rg.341135036 · Cited by 36

The genetics of coronary artery disease

Roberts, R., & Stewart, A. F. R. (2012) · Current Opinion in Cardiology · doi:10.1097/hco.0b013e3283515b4b · Cited by 36

Impact of Genetic Variation on CRISPR-Cas Targeting

Canver, M. C., Joung, J. K., & Pinello, L. (2018) · The CRISPR Journal · doi:10.1089/crispr.2017.0016 · Cited by 36

Molecular mechanisms involved in drug-induced liver injury caused by urate-lowering Chinese herbs: A network pharmacology study and biology experiments

Fan, L., Dong, Y.-Z., Zhang, D., Zhang, X., Lin, Z., & Zhang, B. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216948 · Cited by 39

Identification of key active constituents of Buchang Naoxintong capsules with therapeutic effects against ischemic stroke by using an integrative pharmacology-based approach

Xu, H., Yang, S., Yanqiong, Z., Jia, Q., Li, D., Zhang, Y., Liu, F., & Hongjun, Y. (2015) · Molecular BioSystems · doi:10.1039/c5mb00460h · Cited by 36

Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases

Alsentzer, E., Li, M. M., Kobren, S. N., Noori, A., Undiagnosed Diseases Network, Kohane, I. S., & Zitnik, M. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01749-1 · Cited by 54

Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm

Iwata, M., Yuan, L., Zhao, Q., Tabei, Y., Berenger, F., Sawada, R., Akiyoshi, S., Hamano, M., & Yamanishi, Y. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz313 · Cited by 35

Improvements to CluSTr: the database of SWISS-PROT+TrEMBL protein clusters

Kriventseva, E. V. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg035 · Cited by 35

Identification of the Active Constituents and Significant Pathways of Cangfu Daotan Decoction for the Treatment of PCOS Based on Network Pharmacology

Xu, W., Tang, M., Wang, J., & Wang, L. (2020) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2020/4086864 · Cited by 34

Mapping, Infrastructure, and Data Analysis for the Brazilian Network of Rare Diseases: Protocol for the RARASnet Observational Cohort Study

Alves, D., Yamada, D. B., Bernardi, F. A., Carvalho, I., Filho, M. E. C., Neiva, M. B., Lima, V., & Félix, T. M. (2020) · JMIR Research Protocols · doi:10.2196/24826 · Cited by 35

Prioritizing cancer-related key miRNA-target interactions by integrative genomics

Xiao, Y., Guan, J., Ping, Y., Xu, C., Huang, T., Zhao, H., Fan, H., Li, Y., Lv, Y., Zhao, T., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks538 · Cited by 33

Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications

Duffy, Á., Petrazzini, B. O., Stein, D. F., Park, J. K., Forrest, I. S., Gibson, K., Vy, H. M. T., Chen, R. K., Márquez‐Luna, C., Mort, M. E., et al. (2024) · Nature Genetics · doi:10.1038/s41588-023-01609-2 · Cited by 35

CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature

Praz, V. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh107 · Cited by 33

A survey of web resources and tools for the study of TCM network pharmacology

Zhao, J., Yang, J., Tian, S., & Zhang, W. (2019) · Quantitative Biology · doi:10.1007/s40484-019-0167-8 · Cited by 35

Application of network pharmacology and molecular docking to elucidate the potential mechanism of Eucommia ulmoides-Radix Achyranthis Bidentatae against osteoarthritis

Jian, G., Su, B.-Z., Zhou, W., & Xiong, H. (2020) · BioData Mining · doi:10.1186/s13040-020-00221-y · Cited by 33

Network medicine: linking disorders

Piro, R. M. (2012) · Human Genetics · doi:10.1007/s00439-012-1206-y · Cited by 34

Computational Prediction of Drug-Disease Association Based on Graph-Regularized One Bit Matrix Completion

Mongia, A., Chouzenoux, É., & Majumdar, A. (2022) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3189879 · Cited by 34

Searching for repetitions in biological networks: methods, resources and tools

Panni, S., & Rombo, S. E. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbt084 · Cited by 32

Genes2FANs: connecting genes through functional association networks

Dannenfelser, R., Clark, N. R., & Ma’ayan, A. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-156 · Cited by 31

Disease gene classification with metagraph representations

Ata, S. K., Fang, Y., Wu, M., Li, X., & Xiao, X. (2017) · Methods · doi:10.1016/j.ymeth.2017.06.036 · Cited by 32

Large-Scale Elucidation of Drug Response Pathways in Humans

Silberberg, Y., Gottlieb, A., Kupiec, M., Ruppin, E., & Sharan, R. (2012) · Journal of Computational Biology · doi:10.1089/cmb.2011.0264 · Cited by 31

Distinct and Competitive Regulatory Patterns of Tumor Suppressor Genes and Oncogenes in Ovarian Cancer

Zhao, M., Sun, J., & Zhao, Z. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044175 · Cited by 32

C/VDdb: A multi-omics expression profiling database for a knowledge-driven approach in cardiovascular disease (CVD)

Fernandes, M., Patel, A., & Husi, H. (2018) · PLoS ONE · doi:10.1371/journal.pone.0207371 · Cited by 32

Deoxythymidylate kinase, DTYMK, is a novel gene for mitochondrial DNA depletion syndrome

Lam, C., Yeung, W.-L., Ling, T.-K., Wong, K.-C., & Law, C. Y. (2019) · Clinica Chimica Acta · doi:10.1016/j.cca.2019.06.028 · Cited by 31

Pharmacological mechanism of Shenlingbaizhu formula against experimental colitis

Yu, W., Wang, G., Lu, C., Liu, C., Jiang, L., Jiang, Z., Liang, Z., Wang, X., Qin, Z., & Yan, J. (2022) · Phytomedicine · doi:10.1016/j.phymed.2022.153961 · Cited by 31

Oral Cancer-related Inherited Cancer Syndromes: A Comprehensive Review

Batra, A., & Yerawadekar, S. A. (2016) · The Journal of Contemporary Dental Practice · doi:10.5005/jp-journals-10024-1880 · Cited by 30

Predicting circRNA-disease associations based on autoencoder and graph embedding

Yang, J., & Lei, X. (2021) · Information Sciences · doi:10.1016/j.ins.2021.04.073 · Cited by 30

CGMIM: Automated text-mining of Online Mendelian Inheritance in Man (OMIM) to identify genetically-associated cancers and candidate genes

Bajdik, C. D., Kuo, B. Y.-L., Rusaw, S., Jones, S. J. M., & Brooks-Wilson, A. R. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-78 · Cited by 30

Exploring Alternative Models for Sex-Linked Quantitative Trait Loci in Outbred Populations: Application to an Iberian × Landrace Pig Intercross

Miguel Pérez-enciso, A., Clop, A., Folch, J. M., Sánchez, A., Oliver, M. A., Óvilo, C., Barragán, C., Varona, L., & Noguera, J. L. (2002) · Genetics · doi:10.1093/genetics/161.4.1625 · Cited by 30

Whole Genome Sequencing Analysis

Yin, R., Kwoh, C. K., & Zheng, J. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809633-8.20095-2 · Cited by 30

Blood type, ABO genetic variants, and ovarian cancer survival

Cozzi, G. D., Levinson, R. T., Toole, H., Snyder, M.-R. B., Deng, A., Crispens, M. A., Khabele, D., & Beeghly-Fadiel, A. C. (2017) · PLoS ONE · doi:10.1371/journal.pone.0175119 · Cited by 30

The role of the Human Metabolome Database in inborn errors of metabolism

Mandal, R., Chamot, D., & Wishart, D. S. (2018) · Journal of Inherited Metabolic Disease · doi:10.1007/s10545-018-0137-8 · Cited by 30

Integrated phytochemical analysis based on UHPLC-LTQ–Orbitrap and network pharmacology approaches to explore the potential mechanism of Lycium ruthenicum Murr. for ameliorating Alzheimer's disease

Luo, Z., Yu, G., Chen, X., Liu, Y., Zhou, Y., Wang, G., & Shi, Y. (2020) · Food & Function · doi:10.1039/c9fo02840d · Cited by 29

Disease gene prediction with privileged information and heteroscedastic dropout

Shu, J., Li, Y., Wang, S., Xi, B., & Ma, J. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab310 · Cited by 29

Identifying disease-gene associations using a convolutional neural network-based model by embedding a biological knowledge graph with entity descriptions

Choi, W., & Lee, H. (2021) · PLoS ONE · doi:10.1371/journal.pone.0258626 · Cited by 28

Genetics of Coronary Artery Disease in the 21st Century

Roberts, R., & Stewart, A. F. R. (2012) · Clinical Cardiology · doi:10.1002/clc.22002 · Cited by 30

Variable locus length in the human genome leads to ascertainment bias in functional inference for non-coding elements

Taher, L., & Ovcharenko, I. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp043 · Cited by 30

Primary immunodeficiency registries

Knerr, V., & Grimbacher, B. (2007) · Current Opinion in Allergy and Clinical Immunology · doi:10.1097/aci.0b013e3282f2162c · Cited by 29

Prediction of the Coding Sequences of Mouse Homologues of KIAA Gene: III. The Complete Nucleotide Sequences of 500 Mouse KIAA-homologous cDNAs Identified by Screening of Terminal Sequences of cDNA Clones Randomly Sampled from Size-fractionated Libraries

Okazaki, N. (2003) · DNA Research · doi:10.1093/dnares/10.4.167 · Cited by 29

A systems biology investigation of neurodegenerative dementia reveals a pivotal role of autophagy

Caberlotto, L., & Nguyen, T.-P. (2014) · BMC Systems Biology · doi:10.1186/1752-0509-8-65 · Cited by 27

A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations

Guo, X., Gao, L., Wei, C., Yang, X., Zhao, Y. C., & Dong, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024171 · Cited by 28

Global gene expression analysis of cell-free RNA in amniotic fluid from women destined to develop preeclampsia

Jung, Y. W., Shim, J. I., Shim, S. H., Shin, Y.-J., Shim, S. H., Chang, S. W., & Cha, D. H. (2019) · Medicine · doi:10.1097/md.0000000000013971 · Cited by 27

State of the art and open challenges in community-driven knowledge curation

Groza, T., Tudorache, T., & Dumontier, M. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.11.007 · Cited by 27

Network Pharmacology-Based Approach Combined with Bioinformatic Analytics to Elucidate the Potential of Curcumol against Hepatocellular Carcinoma

Huang, X., Rehman, H. M., Szöllősi, A. G., & Zhou, S. (2022) · Genes · doi:10.3390/genes13040653 · Cited by 27

IDR knowledge base for primary immunodeficiencies

Samarghitean, C., Väliaho, J., & Vihinen, M. (2007) · Immunome Research · doi:10.1186/1745-7580-3-6 · Cited by 27

Dependency Pattern Models for Information Extraction

Stevenson, M., & Greenwood, M. (2009) · Research on Language and Computation · doi:10.1007/s11168-009-9061-2 · Cited by 27

New friendly tools for users of ESTHER, the database of the α/β-hydrolase fold superfamily of proteins

Renault, L. L. R., Nègre, V., Hôtelier, T., Cousin, X., Marchot, P., & Chatonnet, A. (2005) · Chemico-Biological Interactions · doi:10.1016/j.cbi.2005.10.100 · Cited by 27

Oral Fibroblast Expression of wound-inducible transcript 3.0 (wit3.0) Accelerates the Collagen Gel Contraction in Vitro

Sukotjo, C., Lin, A., Song, K., Ogawa, T., Wu, B. M., & Nishimura, I. (2003) · Journal of Biological Chemistry · doi:10.1074/jbc.m309616200 · Cited by 27

Bioinformatics methods for identifying candidate disease genes

van Driel, M. A., & Brunner, H. G. (2006) · Human Genomics · doi:10.1186/1479-7364-2-6-429 · Cited by 27

UCbase 2.0: ultraconserved sequences database (2014 update)

Lomonaco, V., Martoglia, R., Mandreoli, F., Anderlucci, L., Emmett, W., Bicciato, S., & Taccioli, C. (2014) · Database · doi:10.1093/database/bau062 · Cited by 26

A tailored approach to fusion transcript identification increases diagnosis of rare inherited disease

Oliver, G. R., Tang, X., Schultz‐Rogers, L. E., Vidal‐Folch, N., Jenkinson, W. G., Schwab, T. L., Gaonkar, K. S., Cousin, M. A., Nair, A., Basu, S., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0223337 · Cited by 26

Integrating network pharmacology and pharmacological validation to explore the effect of Shi Wei Ru Xiang powder on suppressing hyperuricemia

Li, Q., Liu, P., Wu, C., Bai, L., Zhang, Z., Bao, Z., Zou, M., Ren, Z., Lin, Y., Liao, M., et al. (2022) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2022.115679 · Cited by 26

SNP@Domain: a web resource of single nucleotide polymorphisms (SNPs) within protein domain structures and sequences

Han, A., Kang, H. J., Cho, Y., Lee, S., Kim, Y., & Gong, S. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl323 · Cited by 26

GPCRs, G-proteins, effectors and their interactions: human-gpDB, a database employing visualization tools and data integration techniques

Satagopam, V., Theodoropoulou, M. C., Stampolakis, C. K., Pavlopoulos, G. A., Papandreou, N. C., Bagos, P. G., Schneider, R., & Hamodrakas, S. J. (2010) · Database · doi:10.1093/database/baq019 · Cited by 26

Moby and Moby 2: Creatures of the Deep (Web)

Vandervalk, B. P., McCarthy, E. L., & Wilkinson, M. D. (2009) · Briefings in Bioinformatics · doi:10.1093/bib/bbn051 · Cited by 26

Voltage-dependent calcium channels in mammalian spermatozoa revisited

Benoff, S. H. (2006) · Frontiers in bioscience · doi:10.2741/2158 · Cited by 26

From biological databases to platforms for biomedical discovery

Navarro, J. D., Niranjan, V., Peri, S., Jonnalagadda, C. K., & Pandey, A. (2003) · Trends in biotechnology · doi:10.1016/s0167-7799(03)00108-2 · Cited by 26

Autosomal-dominant primary immunodeficiencies

Lawrence, T. C., Puel, A., Reichenbach, J., Ku, C., Chapgier, A. L. A., Renner, E. D., Minard-Colin, V., Ouache, M., & Casanova, J. (2004) · Current Opinion in Hematology · doi:10.1097/01.moh.0000149609.37309.0a · Cited by 25

The Solution Structure of DNA-free Pax-8 Paired Box Domain Accounts for Redox Regulation of Transcriptional Activity in the Pax Protein Family

Codutti, L., van Ingen, H., Vascotto, C., Fogolari, F., Corazza, A., Tell, G., Quadrifoglio, F., Viglino, P., Boelens, R., & Esposito, G. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m805717200 · Cited by 25

PDbase: a database of Parkinson's Disease-related genes and genetic variation using substantia nigra ESTs

Yang, J. O., Kim, W.-Y., Jeong, S., Oh, J., Jho, S., Bhak, J., & Kim, N.-S. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-s3-s32 · Cited by 25

Functional/activity network (FAN) analysis of gene-phenotype connectivity liaised by grape polyphenol resveratrol

Hsieh, T., Wu, S.-T., Bennett, D. J., Doonan, B. B., Wu, E., & WU, J. M. (2016) · Oncotarget · doi:10.18632/oncotarget.9578 · Cited by 24

Genetics of premature myocardial infarction

Roberts, R. (2008) · Current Atherosclerosis Reports · doi:10.1007/s11883-008-0030-2 · Cited by 23

An en masse phenotype and function prediction system for Mus musculus

Taşan, M., Tian, W., Hill, D. P., Gibbons, F. D., Blake, J. A., & Roth, F. P. (2008) · Genome biology · doi:10.1186/gb-2008-9-s1-s8 · Cited by 24

From phenotype to genotype: issues in navigating the available information resources.

Mitchell, J. A., McCray, A. T., & Bodenreider, O. (2003) · PubMed · doi:10.1267/meth03050557 · Cited by 24

Cornuside improves murine autoimmune hepatitis through inhibition of inflammatory responses

Wang, L., Yan, F., Zhang, J., Xiao, Y., Wang, C., Zhu, Y., Li, C., Liu, Z., Li, W., Wang, C., et al. (2023) · Phytomedicine · doi:10.1016/j.phymed.2023.155077 · Cited by 23

Cognitive Impairments of Sleep-Deprived Ovariectomized (OVX) Female Rats by Voluntary Exercise

Rajizadeh, M. A., Esmaeilpour, K., Motamedy, S., Borzadaran, F. M., & Sheibani, V. (2020) · Basic and Clinical Neuroscience Journal · doi:10.32598/bcn.9.10.505 · Cited by 26

Predicting Drug-Disease Association Based on Ensemble Strategy

Wang, J., Wang, W., Yan, C., Luo, J., & Zhang, G. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.666575 · Cited by 23

RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers

Lazzarini, N., & Bacardit, J. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1729-2 · Cited by 23

Improving data workflow systems with cloud services and use of open data for bioinformatics research

Karim, M. R., Michel, A. M., Zappa, A., Baranov, P. V., Sahay, R., & Rebholz‐Schuhmann, D. (2017) · Briefings in Bioinformatics · doi:10.1093/bib/bbx039 · Cited by 23

EICO (Expression-based Imprint Candidate Organizer): finding disease-related imprinted genes

Nikaido, I. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh093 · Cited by 23

Fusing graph transformer with multi-aggregate GCN for enhanced drug–disease associations prediction

He, S., Yun, L., & Yi, H.-C. (2024) · BMC Bioinformatics · doi:10.1186/s12859-024-05705-w · Cited by 22

Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study

Wang, Y., Sui, Y., Yao, J., Jiang, H., Tian, Q., Tang, Y., Ou, Y., Tang, J. P., & Tan, N. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae362 · Cited by 22

Heterogeneous network propagation for herb target identification

Yang, K., Liu, G., Wang, N., Zhang, R., Yu, J. Q., Chen, J., & Zhou, X. (2018) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-018-0592-z · Cited by 22

Computational Methods for Prediction of Human Protein-Phenotype Associations: A Review

Liu, L., & Zhu, S. (2021) · Phenomics · doi:10.1007/s43657-021-00019-w · Cited by 22

Network‐Based Approaches for Drug Repositioning

Song, T., Wang, G., Ding, M., Rodríguez‐Patón, A., Wang, X., & Wang, S. (2021) · Molecular Informatics · doi:10.1002/minf.202100200 · Cited by 25

New Onto-Tools: Promoter-Express, nsSNPCounter and Onto-Translate

Khatri, P., Desai, V., Tarca, A. L., Sellamuthu, S., Wildman, D. E., Romero, R. J., & Drăghici, S. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl213 · Cited by 22

New perspectives: systems medicine in cardiovascular disease

Krämer, F., Just, S., & Zeller, T. (2018) · BMC Systems Biology · doi:10.1186/s12918-018-0579-5 · Cited by 25

Network-based characterization of disease–disease relationships in terms of drugs and therapeutic targets

Iida, M., Iwata, M., & Yamanishi, Y. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa439 · Cited by 22

Using Genomic Databases for Sequence-Based Biological Discovery

Baxevanis, A. D. (2003) · Molecular Medicine · doi:10.1007/bf03402130 · Cited by 22

Indexing pharmacogenetic knowledge on the World Wide Web

Altman, R. B., Flockhart, D. A., Sherry, S. T., Oliver, D. E., Rubin, D. L., & Klein, T. E. (2003) · Pharmacogenetics · doi:10.1097/00008571-200301000-00002 · Cited by 22

Jumping on the Train of Personalized Medicine: A Primer for Non- Geneticist Clinicians: Part 3. Clinical Applications in the Personalized Medicine Area

Li, A., & Meyre, D. (2014) · Current Psychiatry Reviews · doi:10.2174/1573400510666140630170549 · Cited by 23

DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier

Kulmanov, M., & Hoehndorf, R. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008453 · Cited by 22

Multiple SNP Set Analysis for Genome‐Wide Association Studies Through Bayesian Latent Variable Selection

Lu, Z., Hongtu Zhu, B., Knickmeyer, R. C., Sullivan, P. F., Williams, S., Zou, F., & Initiative, A. D. N. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21932 · Cited by 22

Pathway Palette: A rich internet application for peptide‐, protein‐ and network‐oriented analysis of MS data

Askenazi, M., Li, S., Singh, S., & Marto, J. A. (2010) · PROTEOMICS · doi:10.1002/pmic.200900723 · Cited by 21

Mutation nomenclature extensions and suggestions to describe complex mutations: A discussion

den Dunnen, J. T., & Antonarakis, S. E. (2000) · Human Mutation · doi:10.1002/(sici)1098-1004(200001)15:1 · Cited by 1,757

Online Mendelian Inheritance in Man

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