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

AIDDISON: Empowering Drug Discovery with AI/ML and CADD Tools in a Secure, Web-Based SaaS Platform

Rusinko, A., Rezaei, M. A., Friedrich, L., Buchstaller, H., Kühn, D., & Ghogare, A. A. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c01016 · Cited by 27

Anesthetic drug discovery with computer-aided drug design and machine learning

Liu, X., Xue, Z., Luo, M., Ke, B., & Lv, J. (2024) · Anesthesiology and Perioperative Science · doi:10.1007/s44254-023-00047-x · Cited by 30

Machine Learning-Guided Prediction of Cocrystals Using Point Cloud-Based Molecular Representation

Ahmadi, S., Ghanavati, M. A., & Rohani, S. (2024) · Chemistry of Materials · doi:10.1021/acs.chemmater.3c01437 · Cited by 26

Spotlight on G-Quadruplexes: From Structure and Modulation to Physiological and Pathological Roles

dell’Oca, M. C., Quadri, R., Bernini, G. M., Menin, L., Grasso, L., Rondelli, D., Yazici, O., Sertic, S., Marini, F., Pellicioli, A., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25063162 · Cited by 35

Cucurbitacin B targets STAT3 to induce ferroptosis in non-small cell lung cancer

Zeng, Z., Hu, Y., Xiang, J., Su, J., Tan, H., Lai, T., Chen, X., Fang, G., Li, L., & Luo, L. (2024) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2024.176805 · Cited by 27

Identification of potent inhibitors of HDAC2 from herbal products for the treatment of colon cancer: Molecular docking, molecular dynamics simulation, MM/GBSA calculations, DFT studies, and pharmacokinetic analysis

Khanal, M., Acharya, A., Maharjan, R., Gyawali, K., Adhikari, R., Mulmi, D. D., Lamichhane, T. R., & Lamichhane, H. P. (2024) · PLoS ONE · doi:10.1371/journal.pone.0307501 · Cited by 27

Conformational Space Profiling Enhances Generic Molecular Representation for AI‐Powered Ligand‐Based Drug Discovery

Wang, L., Wang, S., Yang, H., Li, S., Wang, X., Zhou, Y., Tian, S., Liu, L., & Bai, F. (2024) · Advanced Science · doi:10.1002/advs.202403998 · Cited by 27

Peptide-Aware Chemical Language Model Successfully Predicts Membrane Diffusion of Cyclic Peptides

Feller, A. L., & Wilke, C. O. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01441 · Cited by 33

Therapeutic target database 2026: facilitating targeted therapies and precision medicine

Zhang, Y., Zhou, Y., Xu, H., Jiang, W., Li, B., Lai, D., Wan, C., Wang, S., Zhao, M., Tan, Y. C., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1154 · Cited by 35

MolBook UNIPI─Create, Manage, Analyze, and Share Your Chemical Data for Free

Galati, S., Stefano, M. D., Macchia, M., Poli, G., & Tuccinardi, T. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00278 · Cited by 27

Adding open spectral data to MassBank and PubChem using open source tools to support non-targeted exposomics of mixtures

Elapavalore, A., Kondić, T., Singh, R. R., Shoemaker, B. A., Thiessen, P. A., Zhang, J., Bolton, E., & Schymanski, E. (2023) · Environmental Science Processes & Impacts · doi:10.1039/d3em00181d · Cited by 27

Applications of machine learning in microbial natural product drug discovery

Arnold, A., Alexander, J., Liu, G., & Stokes, J. M. (2023) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2023.2251400 · Cited by 30

A Robust Drug–Target Interaction Prediction Framework with Capsule Network and Transfer Learning

Huang, Y., Huang, H., Chen, Y.-G., Lin, Y.-C.-D., Yao, L., Lin, T., Leng, J., Chang, Y., Zhang, Y., Zhu, Z., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241814061 · Cited by 28

A comprehensive dataset on cytotoxicity of ionic liquids

Arakelyan, L. A., Arkhipova, D. M., Seitkalieva, M. M., Vavina, A. V., Sahharova, L. T., Kurbanalieva, S., Posvyatenko, A. V., Egorova, K. S., & Ananikov, V. P. (2024) · Scientific Data · doi:10.1038/s41597-024-04190-3 · Cited by 27

Cross-linked enzyme aggregates of polyethylene terephthalate hydrolyse (PETase) from Ideonella sakaiensis for the improvement of plastic degradation

Lee, Y. L., Jaafar, N. R., Ling, J. G., Huyop, F., Bakar, F. D. A., Rahman, R. A., & Illias, R. M. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.130284 · Cited by 26

DrugRepoBank: a comprehensive database and discovery platform for accelerating drug repositioning

Huang, Y., Dong, D., Zhang, W., Wang, R., Lin, Y.-C.-D., Zuo, H., Huang, H., & Huang, H. (2024) · Database · doi:10.1093/database/baae051 · Cited by 26

The journey of antibody-drug conjugates for revolutionizing cancer therapy: A review

Akram, F., Ali, A. M., Akhtar, M. T., Fatima, T., Shabbir, I., & Haq, I. U. (2024) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2024.118010 · Cited by 30

Orientin alleviates chondrocyte senescence and osteoarthritis by inhibiting PI3K/AKT pathway

Chen, H., Liu, S., Xing, J., Wen, Y.-X., & Chen, L.-B. (2025) · Bone & Joint Research · doi:10.1302/2046-3758.143.bjr-2023-0383.r2 · Cited by 24

The Role of Plant-Derived Natural Products in the Management of Inflammatory Bowel Disease—What Is the Clinical Evidence So Far?

Davila, M., & Papada, E. (2023) · Life · doi:10.3390/life13081703 · Cited by 26

Comparison and evaluation of L. reuteri and L. rhamnosus-fermented egg yolk on the physicochemical and flavor properties of cookies

Jia, J., Deng, X., Jia, X., Guo, C., Liu, X., Liu, Y., & Duan, X. L. (2023) · Food Chemistry X · doi:10.1016/j.fochx.2023.101096 · Cited by 26

Unlocking the Potential of Generative Artificial Intelligence in Drug Discovery

Romanelli, V., Cerchia, C., & Lavecchia, A. (2024) · Springer eBooks · doi:10.1007/978-3-031-46238-2_3 · Cited by 29

Cracking Spirulina Flavor: Compounds, Sensory Evaluations, and Solutions

Braga-Souto, R. N., Bürck, M., Nakamoto, M. M., & Braga, A. R. C. (2025) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2024.104847 · Cited by 25

Quantum-selected configuration interaction: Classical diagonalization of Hamiltonians in subspaces selected by quantum computers

Kanno, K., Kohda, M., Imai, R., Koh, S., Mitarai, K., Mizukami, W., & Nakagawa, Y. O. (2026) · Physical Review Research · doi:10.1103/dmn4-snfx · Cited by 162

Virtual Screening of Small Molecules Targeting BCL2 with Machine Learning, Molecular Docking, and MD Simulation

Tondar, A., Sánchez-Herrero, S., Bepari, A. K., Bahmani, A. H., Calvet, L., & Hervás, D. (2024) · Biomolecules · doi:10.3390/biom14050544 · Cited by 26

Data-Driven Design of Flexible Metal–Organic Frameworks for Gas Storage

Lim, Y., Kim, B., & Kim, J. (2024) · Chemistry of Materials · doi:10.1021/acs.chemmater.4c00398 · Cited by 26

Novel Strategies Enhancing Bioavailability and Therapeutical Potential of Silibinin for Treatment of Liver Disorders

Šelc, M., Macova, R., & Bábelová, A. (2024) · Drug Design Development and Therapy · doi:10.2147/dddt.s483140 · Cited by 26

Efficient analysis of toxicity and mechanisms of Acetyl tributyl citrate on aging with network toxicology and molecular docking strategy

Zheng, Q., Peng, Q., Shen, J., & Liu, H. (2024) · Toxicology · doi:10.1016/j.tox.2024.154009 · Cited by 25

Optimizing drug design by merging generative AI with a physics-based active learning framework

Filella-Mercè, I., Molina, A., Díaz, L., Orzechowski, M., Berchiche, Y. A., Zhu, Y. M., Vilalta-Mor, J., Malo, L., Yekkirala, A. S., Ray, S. S., et al. (2025) · Communications Chemistry · doi:10.1038/s42004-025-01635-7 · Cited by 46

ArkDTA: attention regularization guided by non-covalent interactions for explainable drug–target binding affinity prediction

Gim, M., Choe, J., Baek, S., Park, J., Lee, C., Ju, M., Lee, S., & Kang, J. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad207 · Cited by 29

Exploring the structural and molecular interaction landscape of nirmatrelvir and Mpro complex: The study might assist in designing more potent antivirals targeting SARS-CoV-2 and other viruses

Chakraborty, C., Bhattacharya, M., Alshammari, A., Alharbi, M., Albekairi, T. H., & Zheng, C. (2023) · Journal of Infection and Public Health · doi:10.1016/j.jiph.2023.09.020 · Cited by 25

Reusable and inductively regenerable magnetic activated carbon for removal of organic micropollutants from secondary wastewater effluents

Drenkova-Tuhtan, A., Inskeep, C. S., Luthardt, L., Deuso, S. L., Ballweg, T., Hanselmann, D., Béalu, Z., Meyer, C., Schug, B., Steinmetz, H., et al. (2024) · Water Research · doi:10.1016/j.watres.2024.121525 · Cited by 24

Lentinan attenuates allergic airway inflammation and epithelial barrier dysfunction in asthma via inhibition of the PI3K/AKT/NF-κB pathway

Song, Y., Chen, Y., Cai, H., Zhu, G., Zeng, Y., Abuduxukuer, Z., Chen, K., Wang, J., Ye, L., & Jin, M. (2024) · Phytomedicine · doi:10.1016/j.phymed.2024.155965 · Cited by 24

Longitudinal Exposomics in a Multiomic Wellness Cohort Reveals Distinctive and Dynamic Environmental Chemical Mixtures in Blood

Sdougkou, K., Papazian, S., Bonnefille, B., Xie, H., Edfors, F., Fagerberg, L., Uhlén, M., Bergström, G. M. L., Martin, L. J., & Martin, J. W. (2024) · Environmental Science & Technology · doi:10.1021/acs.est.4c05235 · Cited by 25

A Simple Machine Learning-Based Quantitative Structure–Activity Relationship Model for Predicting pIC50 Inhibition Values of FLT3 Tyrosine Kinase

Alcázar, J. J., Sánchez, I., Merino, C., Monasterio, B., Sajuria, G., Miranda, D., Díaz, F., & Campodónico, P. R. (2025) · Pharmaceuticals · doi:10.3390/ph18010096 · Cited by 24

One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening

Wellnitz, J., Jain, S., Hochuli, J. E., Maxfield, T., Muratov, E. N., Tropsha, A., & Zakharov, A. V. (2025) · Journal of Cheminformatics · doi:10.1186/s13321-025-00948-y · Cited by 33

Large Language Models as Tools for Molecular Toxicity Prediction: AI Insights into Cardiotoxicity

Yang, H., Xiu, J., yan, W., Liu, K., Cui, H., Wang, Z., He, Q., Gao, Y., & Han, W. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01371 · Cited by 27

Kinetic Steering of Amyloid Formation and Polymorphism by Canagliflozin, a Type-2 Diabetes Drug

Taylor, A. I. P., Xu, Y., Wilkinson, M., Chakraborty, P., Brinkworth, A., Willis, L. F., Zhuravleva, A., Ranson, N. A., Foster, R., & Radford, S. E. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.4c16743 · Cited by 25

Structures and mechanism of the human mitochondrial pyruvate carrier

Liang, J., Shi, J., Song, A., Lu, M., Zhang, K., Xu, M. M., Huang, G., Lu, P., Wu, X., & Ma, D. (2025) · Nature · doi:10.1038/s41586-025-08873-8 · Cited by 26

Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches

Lam, J. H., & Katritch, V. (2025) · npj Drug Discovery. · doi:10.1038/s44386-025-00031-4 · Cited by 30

Eight Zhes Decoction ameliorates the lipid dysfunction of nonalcoholic fatty liver disease using integrated lipidomics, network pharmacology and pharmacokinetics

Zhou, Y., Dai, Z., Deng, K., Wang, Y., Ying, J., Chu, D., Zhou, J., & Tang, C. (2023) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2023.05.012 · Cited by 24

LDS-CNN: a deep learning framework for drug-target interactions prediction based on large-scale drug screening

Wang, Y., Zhang, Z., Piao, C., Huang, Y. P., Zhang, Y., Zhang, C., Lu, Y., & Liu, D. (2023) · Health Information Science and Systems · doi:10.1007/s13755-023-00243-w · Cited by 24

Systematic analysis of antimicrobial activity, phytochemistry, and in silico molecular interaction of selected essential oils and their formulations from different Indian spices against foodborne bacteria

Gupta, N., Bhattacharya, S., Urbanová, K., Dutta, A., Hazra, A. K., Fernández-Cusimamani, E., & Leuner, O. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e22480 · Cited by 24

Exploratory studies on chrysin via antioxidant, antimicrobial, ADMET, PASS and molecular docking evaluations

Adesina, A. F., Adewuyi, A., & Otuechere, C. A. (2024) · Pharmacological Research - Modern Chinese Medicine · doi:10.1016/j.prmcm.2024.100413 · Cited by 24

In silico identification of antiviral compounds for the treatment of chikungunya virus infection: qsar modelling and md simulation analysis

Abdulhamza, H. M., Farhan, M. S., Hassan, S. S., Al-Hussaniy, H. A., & Oraibi, A. I. (2024) · Medicine in Novel Technology and Devices · doi:10.1016/j.medntd.2024.100304 · Cited by 24

Adapting physiologically-based pharmacokinetic models for machine learning applications

Habiballah, S., & Reisfeld, B. (2023) · Scientific Reports · doi:10.1038/s41598-023-42165-3 · Cited by 23

PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank

Kunnakkattu, I. R., Choudhary, P., Pravda, L., Nadzirin, N., Smart, O. S., Yuan, Q., Anyango, S., Nair, S. S., Váradi, M., & Velankar, S. S. (2023) · Journal of Cheminformatics · doi:10.1186/s13321-023-00786-w · Cited by 23

Evaluating flavonoids as potential aromatase inhibitors for breast cancer treatment: In vitro studies and in silico predictions

Seo, J. I., Yu, J. S., Zhang, Y., & Yoo, H. H. (2024) · Chemico-Biological Interactions · doi:10.1016/j.cbi.2024.110927 · Cited by 24

Harnessing probiotics capability to combat Salmonella Heidelberg and improve intestinal health in broilers

Hoepers, P. G., Nunes, P. L. F., Almeida-Souza, H. O., Martins, M. M., Carvalho, R. D. D. O., Dreyer, C. T., Aburjaile, F. F., Sommerfeld, S., Azevedo, V., & Fonseca, B. B. (2024) · Poultry Science · doi:10.1016/j.psj.2024.103739 · Cited by 23

MolLM : a unified language model for integrating biomedical text with 2D and 3D molecular representations

Tang, X., Tran, A., Tan, J. T. C., & Gerstein, M. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae260 · Cited by 25

Feasibility study of LOHC-SOFC systems under dynamic behavior for cargo ships compared to ammonia alternatives

Gambini, M., Guarnaccia, F., Manno, M., & Vellini, M. (2024) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2024.07.224 · Cited by 23

Sea buckthorn and its flavonoids isorhamnetin, quercetin, and kaempferol favorably influence bone and breast tissue health

Martiniaková, M., Pénzes, N., Bíro, R., Šarocká, A., Kováčová, V., Mondočková, V., Čierniková, S., & Omelka, R. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1462823 · Cited by 24

Conformalized Graph Learning for Molecular ADMET Property Prediction and Reliable Uncertainty Quantification

Li, P., Hua, L., Ma, Z., Hu, W., Liu, Y., & Zhu, J. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01139 · Cited by 27

Approaching coupled-cluster accuracy for molecular electronic structures with multi-task learning

Tang, H., Xiao, B., He, W., Subašić, P., Harutyunyan, A. R., Wang, Y., Liu, F., Xu, H., & Li, J. (2024) · Nature Computational Science · doi:10.1038/s43588-024-00747-9 · Cited by 28

Lipid nutritional variances in thermal-treated egg yolks and their influence on flavor formation

Zhou, Z., Jing, G., Wang, L., Cui, S., Qin, L., & Huang, X. (2025) · Food Chemistry · doi:10.1016/j.foodchem.2025.143185 · Cited by 23

Transformer-Based Models for Predicting Molecular Structures from Infrared Spectra Using Patch-Based Self-Attention

Wu, W., Leonardis, A., Jiao, J., Jiang, J., & Chen, L. (2025) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.4c05665 · Cited by 25

In silico methods for drug-target interaction prediction

Ru, X., Xu, L., Wu, H., & Zou, Q. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101184 · Cited by 26

Isolation of Novel Bacterial Strains Pseudomonas extremaustralis CSW01 and Stutzerimonas stutzeri CSW02 from Sewage Sludge for Paracetamol Biodegradation

Vargas-Ordóñez, A., Aguilar-Romero, I., Capellán, J. V., Madrid, F., & González, E. M. (2023) · Microorganisms · doi:10.3390/microorganisms11010196 · Cited by 23

Exploring the mechanism of Suanzaoren decoction in treatment of insomnia based on network pharmacology and molecular docking

Wang, S., Yan, Z., & Hu, X. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1145532 · Cited by 23

Molecular interaction between myofibrillar protein and beta-carotene during heating

Zhou, T., Liu, H., Diao, X., Zhao, Q., Duan, J., Ibeogu, I. H., Yar, M. S., Wu, J., & Li, C. (2023) · Food Chemistry · doi:10.1016/j.foodchem.2023.137588 · Cited by 23

Identifying priority PBT-like compounds from emerging PFAS by nontargeted analysis and machine learning models

Han, B.-C., Liu, J.-S., Bizimana, A., Zhang, B.-X., Kateryna, S., Zhao, Z., Yu, L., Shen, Z.-Z., & Meng, X. (2023) · Environmental Pollution · doi:10.1016/j.envpol.2023.122663 · Cited by 26

Ginger beer derived from back-slopping: Volatile compounds, microbial communities on activation and fermentation, metabolites and sensory characteristics

de Oliveira, L. I. G., da Costa, W. K. A., de Oliveira, F. D. C., Bezerril, F. F., Eireli, L. P. A. M., Lima, M. D. S., Noronha, M. F., Cabral, L., Wagner, R. C., Pimentel, T. C., et al. (2023) · Food Chemistry · doi:10.1016/j.foodchem.2023.137640 · Cited by 23

INTEDE 2.0: the metabolic roadmap of drugs

Zhang, Y., Liu, X., Li, F., Yin, J., Yang, H., Li, X., Liu, X., Chai, X., Niu, T., Zeng, S., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1013 · Cited by 23

Exploring the therapeutic potential of quercetin in cancer treatment: Targeting long non-coding RNAs

Sheikhnia, F., Fazilat, A., Rashidi, V., Azizzadeh, B., Mohammadi, M., Maghsoudi, H., & Majidinia, M. (2024) · Pathology - Research and Practice · doi:10.1016/j.prp.2024.155374 · Cited by 25

REINVENT4: Modern AI–Driven Generative Molecule DesignPreprint

Loeffler, H. H., He, J., Tibo, A., Janet, J. P., Voronov, A., Mervin, L., & Engkvist, O. (2023) · ChemRxiv · doi:10.26434/chemrxiv-2023-xt65x · Cited by 23

New methods for drug synergy prediction: A mini-review

Abbasi, F., & Rousu, J. (2024) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2024.102827 · Cited by 22

Machine learning methods for compound annotation in non‐targeted mass spectrometry—A brief overview of fingerprinting, in silico fragmentation and de novo methods

Russo, F. F., Nowatzky, Y., Jaeger, C., Parr, M. K., Benner, P., Muth, T., & Lisec, J. (2024) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.9876 · Cited by 27

Mendelian randomization reveals potential causal relationships between cellular senescence-related genes and multiple cancer risks

Qiu, X., Guo, R., Wang, Y., Zheng, S., Wang, B., & Gong, Y. (2024) · Communications Biology · doi:10.1038/s42003-024-06755-9 · Cited by 22

MCF classifier: Estimating, standardizing, and stratifying medicine carbon footprints, at scale

Taylor, H., Mahamdallie, S., Sawyer, M. H., & Rahman, N. (2024) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.16229 · Cited by 22

Quercetin inhibits mitophagy-mediated apoptosis and inflammatory response by targeting the PPARγ/PGC-1α/NF-κB axis to improve acute liver failure

Wu, H., Wu, L., Luo, L., Wu, Y., Zhang, Q., Li, H., & Zhang, B.-F. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.113444 · Cited by 26

Advanced transformer models for structure-property relationship predictions of ionic liquid melting points

Khambhawala, A., Lee, C. H., Pahari, S., Nancarrow, P., Jabbar, N. A., El‐Halwagi, M. M., & Kwon, J. S. (2024) · Chemical Engineering Journal · doi:10.1016/j.cej.2024.158578 · Cited by 22

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Elapavalore, A., Ross, D. H., Grouès, V., Aurich, D., Krinsky, A. M., Kim, S., Thiessen, P. A., Zhang, J., Dodds, J. N., Baker, E. S., et al. (2025) · Environmental Science & Technology Letters · doi:10.1021/acs.estlett.4c01003 · Cited by 27

Tracking protein kinase targeting advances: integrating QSAR into machine learning for kinase-targeted drug discovery

Shahin, R. O., Jaafreh, S. M., & Azzam, Y. (2025) · Future Science OA · doi:10.1080/20565623.2025.2483631 · Cited by 23

Gut microbiome-mediated transformation of dietary phytonutrients is associated with health outcomes

Zhang, L., Marfil-Sánchez, A., Kuo, T.-H., Seelbinder, B., van Dam, L., Depetris-Chauvin, A., Jahn, L. J., Sommer, M. O. A., Zimmermann, M., Ni, Y., et al. (2025) · Nature Microbiology · doi:10.1038/s41564-025-02197-z · Cited by 28

Photodynamic therapy of cervical cancer: a scoping review on the efficacy of various molecules

Shanazarov, N. A., Zare, A., Mussin, N. M., Albayev, R. K., Kaliyev, A. A., Iztleuov, Y. M., Smailova, S. B., & Tamadon, A. (2024) · Therapeutic Advances in Chronic Disease · doi:10.1177/20406223241233206 · Cited by 22

Emission of volatile organic compounds during open fire cooking with wood biomass: Traditional three-stone open fire vs. gasifier cooking stove in rural Kenya

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