PubChem 2023 update

Gene Ontology: tool for the unification of biology

Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206

Database resources of the National Center for Biotechnology Information: update

Wheeler, D. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh073 · Cited by 10,695

SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

Weininger, D. (1988) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci00057a005 · Cited by 7,436

UniProt: the universal protein knowledgebase in 2021

The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Agivetova, R., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1100 · Cited by 6,372

Database resources of the National Center for Biotechnology Information

Agarwala, R., Barrett, T., Beck, J., Benson, D., Bollin, C., Bolton, E. E., Bourexis, D., Brister, J., Bryant, S. H., Canese, K., et al. (2017) · Nucleic Acids Res. · doi:10.1093/nar/gkx1095 · Cited by 6,277

PubChem Substance and Compound databases

Kim, S., Thiessen, P. A., Bolton, E. E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv951 · Cited by 5,436

PubChem in 2021: new data content and improved web interfaces

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa971 · Cited by 3,953

The Gene Ontology resource: enriching a GOld mine

The Gene Ontology Consortium, Carbon, S., Douglass, E., Good, B. M., Unni, D. R., Harris, N. L., Mungall, C. J., Basu, S., Chisholm, R. L., Dodson, R. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1113 · Cited by 3,555

PubChem 2019 update: improved access to chemical data

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1033 · Cited by 3,249

NCBI Taxonomy: a comprehensive update on curation, resources and tools

Schoch, C. L., Ciufo, S., Domrachev, M., Hotton, C. L., Kannan, S., Khovanskaya, R., Leipe, D., Mcveigh, R., O’Neill, K., Robbertse, B., et al. (2020) · Database · doi:10.1093/database/baaa062 · Cited by 2,635

Mechanism of norcantharidin intervention in gastric cancer: analysis based on antitumor proprietary Chinese medicine database, network pharmacology, and transcriptomics

Zhai, Y., Zhang, F., Zhou, J., Qiao, C., Jin, Z., Zhang, J., Wu, C., Shi, R., Huang, J., Gao, Y., et al. (2024) · Chinese Medicine · doi:10.1186/s13020-024-01000-1 · Cited by 11

Network Pharmacology, Molecular Dynamics and In Vitro Assessments of Indigenous Herbal Formulations for Alzheimer’s Therapy

Ojo, O. A., Ajayi-Odoko, O. A., Gyebi, G. A., Ayokunle, D. I., Ogunlakin, A. D., Ezenabor, E. H., Olanrewaju, A. A., Agbeye, O. D., Ogunwale, E. T., Rotimi, D. E., et al. (2024) · Life · doi:10.3390/life14101222 · Cited by 11

Meat Animal Biologics Discovery Opportunities from the Gut Microbiome: Application of Metabolomics

Chatman, C. C., Olson, E. G., Mantovani, H. C., Majumder, E. L.-W., & Ricke, S. C. (2024) · Meat and Muscle Biology · doi:10.22175/mmb.18261 · Cited by 11

Incorporating taste and odour problems in water safety plans

Kožíšek, F., Chorus, I., Testai, E., Kaloudis, T., Akçaalan, R., Albay, M., Steinhaus, M., Bošnjak, M. U., Dunkel, A., Hiskia, A. E., et al. (2024) · Journal of Water and Health · doi:10.2166/wh.2024.166 · Cited by 11

Towards novel small-molecule inhibitors blocking PD-1/PD-L1 pathway: From explainable machine learning models to molecular dynamics simulation

Wu, X., Liang, J., Meng, L., Wang, B., Liu, B., & Jin, Y. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.136325 · Cited by 11

Quantum chemical investigations into the structural and spectroscopic properties of choline chloride-based deep eutectic solvents

Hasan, M. A., Rahman, I. M. M., Hossain, M., & Chowdhury, F. I. (2024) · Chemical Physics Impact · doi:10.1016/j.chphi.2024.100777 · Cited by 11

HDBind: encoding of molecular structure with hyperdimensional binary representations

Jones, D., Zhang, X., Bennion, B. J., Pinge, S., Xu, W., Kang, J., Khaleghi, B., Moshiri, N., Allen, J., & Rosing, T. (2024) · Scientific Reports · doi:10.1038/s41598-024-80009-w · Cited by 12

Development of a QSAR model to predict protein-flavor binding in protein-rich food systems

Barallat-Pérez, C., Hollebrands, B., Janssen, H., Martins, S. I. F. S., Fogliano, V., Hageman, J. A., & Oliviero, T. (2024) · Food Chemistry · doi:10.1016/j.foodchem.2024.142268 · Cited by 11

Mangiferin alleviates Quorum sensing regulated biofilm formation and virulence factor production in pathogenic bacteria: in vitro and in silico investigation

Al‐Shabib, N. A., Husain, F. M., Ashraf, N. M., Arshad, M., Khan, J. M., Khan, A., Adil, M., & Hassan, I. (2024) · Process Biochemistry · doi:10.1016/j.procbio.2024.12.009 · Cited by 11

Unlocking the potential of Traditional Chinese Medicine (TCM): Shipi Xiaoji formula (SPXJF) as a novel ferroptosis inducer in hepatocellular carcinoma

Yang, R., Fu, X., Wang, Z., Xue, P., Wu, L., Tan, X., Peng, W., Li, K., Gao, W., & Zeng, P. (2024) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2024.119236 · Cited by 11

Glucosinolates and Their Hydrolytic Derivatives: Promising Phytochemicals With Anticancer Potential

Joković, N. M., Pešić, S., Vitorović, J., Bogdanović, A., Sharifi‐Rad, J., & Călina, D. C. (2024) · Phytotherapy Research · doi:10.1002/ptr.8419 · Cited by 11

STOUT V2.0: SMILES to IUPAC name conversion using transformer models

Rajan, K., Zielesny, A., & Steinbeck, C. (2024) · Journal of Cheminformatics · doi:10.1186/s13321-024-00941-x · Cited by 14

Bioactive arabinoxylan oligomers via colonic fermentation and enzymatic catalysis: Evidence of interaction with toll-like receptors from in vitro, in silico and functional analysis

Guerreiro, C. D. A., de Andrade, L. A. D., Fernández‐Lainez, C., Fraga, L. N., López‐Velázquez, G., Marques, T. M., do Prado, S. B. R., Brummer, R. J., do Nascimento, J. R. O., & Castro‐Alves, V. (2024) · Carbohydrate Polymers · doi:10.1016/j.carbpol.2024.123175 · Cited by 11

Integrating genetic algorithms and language models for enhanced enzyme design

Teukam, Y. G. N., Zipoli, F., Laino, T., Criscuolo, E., Grisoni, F., & Manica, M. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae675 · Cited by 13

hERGAT: predicting hERG blockers using graph attention mechanism through atom- and molecule-level interaction analyses

Lee, D., & Yoo, S. (2025) · Journal of Cheminformatics · doi:10.1186/s13321-025-00957-x · Cited by 11

Chiral pesticide permethrin promotes the antibiotic resistance genes dissemination by transformation: Different chiral isomers engage in distinct regulatory pathways

Li, C., Wang, L., Dai, Q., Chong, Y., Utsunomiya, S., Wang, H., Han, J., & Han, J. (2025) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2025.137416 · Cited by 11

A prognostic model for lung adenocarcinoma based on cuproptosis and disulfidptosis related genes revealing the key prognostic role of FURIN

You, J., Yu, Q., Chen, R., Li, J., Zhao, T., & Zhong, L. (2025) · Scientific Reports · doi:10.1038/s41598-025-90653-5 · Cited by 13

Predicting Liver-Related In Vitro Endpoints with Machine Learning to Support Early Detection of Drug-Induced Liver Injury

de Lomana, M. G., Gadaleta, D., Raschke, M., Fricke, R., & Montanari, F. (2025) · Chemical Research in Toxicology · doi:10.1021/acs.chemrestox.4c00453 · Cited by 12

SERS-ATB: A comprehensive database server for antibiotic SERS spectral visualization and deep-learning identification

Yuan, Q., Tang, J.-W., Chen, J., Liao, Y., Zhang, W., Wen, X.-R., Liu, X., Chen, H.-J., & Wang, L. (2025) · Environmental Pollution · doi:10.1016/j.envpol.2025.126083 · Cited by 11

Assessing the carcinogenic potential and molecular mechanisms of arecoline in human lungs: from in silico methods to in vitro validation

Wang, W. (2025) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2025.118108 · Cited by 11

Decoding the selective chemical modulation of CYP3A4

Wang, J., Nithianantham, S., Chai, S. C., Jung, K., Yang, L., Ong, H. W., Li, Y., Zhang, Y., Miller, D. J., & Chen, T. (2025) · Nature Communications · doi:10.1038/s41467-025-58749-8 · Cited by 11

Network toxicological analysis of sodium dehydroacetate in food safety

Jin, J., Yan, X. R., & Tian, L. (2025) · Food and Chemical Toxicology · doi:10.1016/j.fct.2025.115469 · Cited by 11

Bioactive Potential of Sweet Cherry (Prunus avium L.) Waste: Antioxidant and Anti-Inflammatory Properties for Sustainable Applications

Frusciante, L., Nyong'a, C. N., Trezza, A., Shabab, B., Olmastroni, T., Barletta, R., Mastroeni, P., Visibelli, A., Orlandini, M., Raucci, L., et al. (2025) · Foods · doi:10.3390/foods14091523 · Cited by 11

A Mamba-based foundation model for materials

Soares, E. A., Brazil, E. V., Shirasuna, V. Y., Zubarev, D. Y., Cerqueira, R., & Schmidt, K. (2025) · npj Artificial Intelligence · doi:10.1038/s44387-025-00009-7 · Cited by 11

Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning

Wang, Y., Li, Y., Liu, L., Hong, P., & Xu, H. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c00430 · Cited by 17

An online GPCR drug discovery resource

Caroli, J., Andreassen, S. N., Lorente, J. S., Xiao, B., Pándy‐Szekeres, G., & Gloriam, D. E. I. (2025) · npj Drug Discovery. · doi:10.1038/s44386-025-00010-9 · Cited by 11

Curated dataset of association constants between a cyclodextrin and a guest for machine learning

Tahıl, G., Delorme, F., Berre, D. L., Monflier, É., Sayede, A., & Tilloy, S. (2023) · Chemical Data Collections · doi:10.1016/j.cdc.2023.101022 · Cited by 11

XMR: an explainable multimodal neural network for drug response prediction

Wang, Z., Zhou, Y., Zhang, Y., Yu, M., & Wang, Y. (2023) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2023.1164482 · Cited by 12

Targeting structural flexibility in low density lipoprotein by integrating cryo-electron microscopy and high-speed atomic force microscopy

Cisse, A., Desfosses, A., Stainer, S., Kandiah, E., Traoré, D. A. K., Bezault, A., Schachner-Nedherer, A.-L., Leitinger, G., Hörl, G., Hinterdorfer, P., et al. (2023) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2023.126345 · Cited by 12

GC-MS Analysis Reveals Unique Chemical Composition of Blumea balsamifera (L.) DC in Ie-Jue Geothermal Area

Maulydia, N. B., Khairan, K., Tallei, T. E., Estevam, E. C., Patwekar, M. F., Fauzi, F. M., & Idroes, R. (2023) · Grimsa Journal of Science Engineering and Technology · doi:10.61975/gjset.v1i1.6 · Cited by 11

From amino acid analysis to improved gel properties: The role of dl-valine in Landaise goose myofibrillar protein

Yan, X., Li, H., Wang, X., Hu, Z., Li, J., Zheng, H., Wang, J., & Zhen, Z. (2024) · Food Chemistry X · doi:10.1016/j.fochx.2024.101123 · Cited by 11

Glycoscience data content in the NCBI Glycans and PubChem

Kim, S., Zhang, J., Cheng, T., Li, Q., & Bolton, E. (2024) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-024-05459-7 · Cited by 11

EnzChemRED, a rich enzyme chemistry relation extraction dataset

Lai, P., Coudert, E., Aimo, L., Axelsen, K. B., Breuza, L., de Castro, E., Feuermann, M., Morgat, A., Pourcel, L., Pedruzzi, I., et al. (2024) · Scientific Data · doi:10.1038/s41597-024-03835-7 · Cited by 15

Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules Versus Therapeutic Peptides

Wang, Y., Ma, Y., Chang, Y.-H., Yan, J., Zhang, J., Cai, M.-Y., & Wei, K. (2025) · Biology · doi:10.3390/biology14121665 · Cited by 11

Essential Oil of Origanum vulgare var. aureum L. from Western Romania: Chemical Analysis, In Vitro and In Silico Screening of Its Antioxidant Activity

Jianu, C., Lukinich-Gruia, A. T., Rădulescu, M., Mioc, M., Mioc, A., Şoica, C., Constantin, A. T., David, I., Bujancă, G. S., & Ghircau-Radu, R. (2023) · Applied Sciences · doi:10.3390/app13085076 · Cited by 10

De Novo Design of Anti-COVID Drugs Using Machine Learning-Based Equivariant Diffusion Model Targeting the Spike Protein

Niranjan, V., Uttarkar, A., Ramakrishnan, A., Muralidharan, A., Shashidhara, A., Acharya, A., Tarani, A., & Kumar, J. (2023) · Current Issues in Molecular Biology · doi:10.3390/cimb45050271 · Cited by 12

Synthesis of silica aerogel films in liquid molds

Bar, G., Amar, L., Marszewski, M., Bolker, A., Dashti, A., Dror, R., & Pilon, L. (2023) · Journal of Colloid and Interface Science · doi:10.1016/j.jcis.2023.06.004 · Cited by 10

SMG-BERT: integrating stereoscopic information and chemical representation for molecular property prediction

Zhang, J., Du, W., Yang, X., Wu, D., Li, J., Wang, K., & Wang, Y. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1216765 · Cited by 11

Biological Synthesis of Copper Nanoparticles Using Edible Plant Allium monanthum: Characterization of Antibacterial, Antioxidant, and Anti-Inflammatory Properties Using In Silico Molecular Docking Analysis

Han, H.-S., Jung, J. S., Jeong, Y., & Choi, K. C. (2023) · Materials · doi:10.3390/ma16206669 · Cited by 10

Multi-technology integrated network pharmacology-based study on phytochemicals, active metabolites, and molecular mechanism of Psoraleae Fructus to promote melanogenesis

Yu, X., Wang, Y., Wu, Z., Jia, M., Xu, Y., Qu, H., Zhao, X., Wang, S., Jing, L., Lou, Y., et al. (2024) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2024.117755 · Cited by 10

Top–down versus bottom–up oxidation of a neonicotinoid pesticide by OH radicals

Wang, X., Wang, W., Wingen, L. M., Perraud, V., & Finlayson‐Pitts, B. J. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2312930121 · Cited by 10

Influence of chlorpyrifos and endosulfan and their metabolites on the virulence of Helicobacter pylori

Singh, S., Varshney, N., Singothu, S., Bhandari, V., & Jha, H. C. (2024) · Environmental Pollution · doi:10.1016/j.envpol.2024.123676 · Cited by 10

Bioactive compounds from Ocimum tenuiflorum and Poria cocos: A novel natural Compound for insomnia treatment based on A computational approach

Ranteh, O., Tedasen, A., Rahman, M. A., Ibrahim, M. A., & Sama‐ae, I. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108491 · Cited by 10

Role of ribosomal pathways and comorbidity in COVID-19: Insight from SARS-CoV-2 proteins and host proteins interaction network analysis

Khan, W. H., Ahmad, R., Alam, R., Khan, N., Rather, I. A., Wani, M. Y., Singh, R. K. B., & Ahmad, A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e29967 · Cited by 9

Colorectal Cancer Detection via Metabolites and Machine Learning

Yang, R., Tsigelny, I. F., Kesari, S., & Kouznetsova, V. L. (2024) · Current Issues in Molecular Biology · doi:10.3390/cimb46050254 · Cited by 10

Anti-inflammatory effect of proanthocyanidins from blueberry through NF-κβ/NLRP3 signaling pathway in vivo and in vitro

Liu, X., Zang, L., Yu, J., Yu, J., Wang, S., Zhou, L., Song, H., Ma, Y., Niu, X., & Li, W. (2024) · Immunopharmacology and Immunotoxicology · doi:10.1080/08923973.2024.2358770 · Cited by 10

Comprehensive analysis of KLF family reveals KLF6 as a promising prognostic and immune biomarker in pancreatic ductal adenocarcinoma

Lin, J., Liu, P., Sun, K., Jiang, L., Liu, Y., Huang, Y., Liu, J., Shi, M., Zhang, J., Wang, T., et al. (2024) · Cancer Cell International · doi:10.1186/s12935-024-03369-3 · Cited by 10

Physiologically based kinetic (PBK) modeling of propiconazole using a machine learning-enhanced read-across approach for interspecies extrapolation

Wu, Y., Sinclair, G., Avanasi, R., & Pecquet, A. M. (2024) · Environment International · doi:10.1016/j.envint.2024.108804 · Cited by 10

A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma

Xu, Y., Li, J., Wang, J., & Deng, F. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-05447-6 · Cited by 12

Rationalizing Diverse Binding Mechanisms to the Same Protein Fold: Insights for Ligand Recognition and Biosensor Design

Leonard, A. C., Friedman, A. J., Chayer, R., Petersen, B. M., Woojuh, J., Xing, Z., Cutler, S. R., Kaar, J. L., Shirts, M. R., & Whitehead, T. A. (2024) · ACS Chemical Biology · doi:10.1021/acschembio.4c00243 · Cited by 9

Towards the prediction of general biomolecular interactions with AI

Baek, M. (2024) · Nature Methods · doi:10.1038/s41592-024-02350-2 · Cited by 10

Human next-generation risk assessment of trichothecene toxicity

Beal, M. A., Habauzit, D., Khoury, L., & Audebert, M. (2024) · Food and Chemical Toxicology · doi:10.1016/j.fct.2024.114916 · Cited by 10

Identification of glycosyltransferases mediating 2‐ O ‐arabinopyranosyl and 2‐ O ‐galactosyl substitutions of glucuronosyl side chains of xylan

Zhong, R., Zhou, D., Phillips, D. R., Adams, E. R., Chen, L., Rose, J. P., Wang, B., & Ye, Z. (2024) · The Plant Journal · doi:10.1111/tpj.16983 · Cited by 10

Mechanism of apoptosis in oral squamous cell carcinoma promoted by cardamonin through PI3K/AKT signaling pathway

Wu, Y., Wang, Y., Han, L., Hu, Q., Xie, Y., Nan, X., He, H., & Liu, Y. (2024) · Scientific Reports · doi:10.1038/s41598-024-71817-1 · Cited by 10

Comparison of in vitro screening methods for evaluating the effects of pharmaceutical excipients on membrane permeability

Morita, T., Yoshida, H., Tomita, N., & Sato, Y. (2024) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2024.124727 · Cited by 10

Prosthetist-Specific Rectification Templates Based on Artificial Intelligence for the Digital Fabrication of Custom Transtibial Sockets

Cutti, A. G., Santi, M. G., Hansen, A. H., Fatone, S., & Residual Limb Shape Capture Group (2024) · Prosthesis · doi:10.3390/prosthesis6050083 · Cited by 10

Exploring the molecular targets of fingolimod and siponimod for treating the impaired cognition of schizophrenia using network pharmacology and molecular docking

Li, C., Zhuo, C., Ma, X., Li, R., Chen, X., Li, Y., Zhang, Q., Yang, L. X., & Wang, L. (2024) · Schizophrenia · doi:10.1038/s41537-024-00504-x · Cited by 10

Curcumin activates the Wnt/β-catenin signaling pathway to alleviate hippocampal neurogenesis abnormalities caused by intermittent hypoxia: A study based on network pharmacology and experimental verification

He, Y., Zhao, Y., Lv, R., Dong, N., Wang, X. D., Yu, Q. P., & Yue, H. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.113299 · Cited by 10

Physics-informed machine learning enabled virtual experimentation for 3D printed thermoplastic

Chen, Z., Wu, Y., Xie, Y., Sattari, K., & Lin, J. (2024) · Materials Horizons · doi:10.1039/d4mh01022a · Cited by 15

Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells

Liu, Z., Petinrin, O. O., Chen, N., Toseef, M., Liu, F., Zhu, Z., Qi, F., & Wong, K. (2024) · BMC Infectious Diseases · doi:10.1186/s12879-024-10000-3 · Cited by 10

PDCdb: the biological activity and pharmaceutical information of peptide–drug conjugate (PDC)

Sun, X., Li, H., Chen, Z., Zhang, Y., Wei, Z., Xu, H., Liao, Y., Jiang, W., Ge, Y., Zheng, L., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae859 · Cited by 10

Exploring the protective effect and molecular mechanism of betulin in Alzheimer's disease based on network pharmacology, molecular docking and experimental validation

Wang, N., Cui, J., Sun, Z., Chen, F., & He, X. (2024) · Molecular Medicine Reports · doi:10.3892/mmr.2024.13356 · Cited by 12

Deciphering the multi-scale mechanism of herbal phytoconstituents in targeting breast cancer: a computational pharmacological perspective

Saini, H., Gupta, P. K., Mahapatra, A. K., Rajagopala, S., Tripathi, R., & Nesari, T. M. (2024) · Scientific Reports · doi:10.1038/s41598-024-75059-z · Cited by 12

An endophenotype network strategy uncovers YangXue QingNao Wan suppresses Aβ deposition, improves mitochondrial dysfunction and glucose metabolism

Wang, X., Yang, J., Zhang, X., Cai, J., Zhang, J., Cai, C., Zhuo, Y., Fang, S., Xu, X., Wang, H., et al. (2024) · Phytomedicine · doi:10.1016/j.phymed.2024.156158 · Cited by 12

Identification of key genes and diagnostic model associated with circadian rhythms and Parkinson’s disease by bioinformatics analysis

Zhang, J., Ma, X., Li, Z., Liu, H., Tian, M., Wen, Y., Wang, S., & Wang, L. (2024) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2024.1458476 · Cited by 9

Exploration of the Bioactivity of Pigmented Extracts from Streptomyces Strains Isolated Along the Banks of the Guaviare and Arauca Rivers (Colombia)

Sarmiento-Tovar, A. A., Prada-Rubio, S. J., Gonzalez-Ronseria, J., Coy-Barrera, E. D., & Díaz, L. E. (2024) · Fermentation · doi:10.3390/fermentation10100529 · Cited by 11

Reductive dehalogenase of Dehalococcoides mccartyi strain CBDB1 reduces cobalt- containing metal complexes enabling anodic respiration

Eberwein, M., Hellmold, N., Frank, R., Deobald, D., & Adrian, L. (2024) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1457014 · Cited by 10

Biocompatible 2D SnSe Nanoflake Employed Enhanced Photocatalytic Degradation of Rhodamine B

Samui, R., Saha, S., Mandal, A. K., & Bhunia, A. K. (2024) · ChemistrySelect · doi:10.1002/slct.202402366 · Cited by 10

Mechanistic exploration of bioactive constituents in Gnetum gnemon for GPCR-related cancer treatment through network pharmacology and molecular docking

Chatatikun, M., Pattaranggoon, N. C., Sama‐ae, I., Ranteh, O., Poolpirom, M., Pantanakong, O., Chumworadet, P., Kawakami, F., Imai, M., & Tedasen, A. (2024) · Scientific Reports · doi:10.1038/s41598-024-75240-4 · Cited by 11

Integrating genomic and molecular data to predict antimicrobial minimum inhibitory concentration in Klebsiella pneumoniae

Ryu, B., Jeon, W., & Kim, D. (2024) · Scientific Reports · doi:10.1038/s41598-024-75973-2 · Cited by 14

In Silico Discovery and Evaluation of Inhibitors of the SARS-CoV-2 Spike Protein–HSPA8 Complex Towards Developing COVID-19 Therapeutic Drugs

Navhaya, L. T., Matsebatlela, T. M., Monama, M. Z., & Makhoba, X. H. (2024) · Viruses · doi:10.3390/v16111726 · Cited by 10

Integrating Metabolomic Analysis, Network Pharmacology, and Molecular Docking to Underlying Pharmacological Mechanism and Ethnobotanical Rationalization for Diabetes Mellitus: Study on Medicinal Plant Fibraurea tinctoria Lour.

Umar, A. H., Widuri, S. A., Sulıstyanıngsıh, Y. C., & Ratnadewi, D. (2024) · Phytochemical Analysis · doi:10.1002/pca.3477 · Cited by 10

A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds

Torabi, M., Haririan, I., Foroumadi, A., Ghanbari, H., & Ghasemi, F. (2024) · SAR and QSAR in environmental research · doi:10.1080/1062936x.2024.2431486 · Cited by 11

Broad range lipidomics and metabolomics coupled with 16S rRNA sequencing to reveal the mechanisms of Huangkui Capsule against cisplatin-induced nephrotoxicity

Liao, J.-C., Xiang, J., Gui, W., Luo, H.-Z., You, Q., He, Q., Lu, M., Yang, S., Wang, Q., Zou, J., et al. (2024) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2024.119197 · Cited by 10

Global Assessment of Emerging Contaminant Removal in Wastewater Treatment Plants: In Silico Hazard Screening and Risk Evaluation

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