Validity of machine learning in biology and medicine increased through collaborations across fields of expertise

A few useful things to know about machine learning

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Increasing value and reducing waste in research design, conduct, and analysis

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Deep learning in bioinformatics

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Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

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Some remarks on protein attribute prediction and pseudo amino acid composition

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Hit and lead generation: beyond high-throughput screening

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Ten quick tips for machine learning in computational biology

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Machine learning in bioinformatics

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Data Sharing

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Ten cheers for interdisciplinarity: The case for interdisciplinary knowledge and research

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Deep learning for biology

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Reproducible research practices, transparency, and open access data in the biomedical literature, 2015–2017

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On the relationship between interdisciplinarity and scientific impact

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Are top-cited papers more interdisciplinary?

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The European Bioinformatics Institute in 2016: Data growth and integration

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The evolution of citation graphs in artificial intelligence research

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What a difference a colon makes: how superficial factors influence subsequent citation

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Data Sharing and theJournal

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Impact measures of interdisciplinary research in physics

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Do interdisciplinary research teams deliver higher gains to science?

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Exploring the interdisciplinary evolution of a discipline: the case of Biochemistry and Molecular Biology

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Protein function in precision medicine: deep understanding with machine learning

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Organization Theory and the Changing Nature of Science

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Quantitative cell biology: the essential role of theory

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Social Media and Research Visibility

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Feature analysis of multidisciplinary scientific collaboration patterns based on PNAS

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Machine learning in the life sciences

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Measuring Scientific Impact Beyond Citation Counts

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ISCB’s Initial Reaction to The New England Journal of Medicine Editorial on Data Sharing

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High-Throughput Translational Medicine: Challenges and Solutions

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Authorship analysis of specialized vs diversified research output

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Authorship analysis of specialized vs diversified research output

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Large language models in medicine

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“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI

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Artificial intelligence and illusions of understanding in scientific research

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SHIFTing artificial intelligence to be responsible in healthcare: a systematic review

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Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology

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Accelerating antibiotic discovery through artificial intelligence

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Digital Reticular Chemistry

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Molecular de-extinction of ancient antimicrobial peptides enabled by machine learning

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ProNA2020 predicts protein–DNA, protein–RNA, and protein–protein binding proteins and residues from sequence

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Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review

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Prevalence and predictors of data and code sharing in the medical and health sciences: systematic review with meta-analysis of individual participant data

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Quantifying the use and potential benefits of artificial intelligence in scientific research

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Recent Advances in Artificial Intelligence-Assisted Ultrasound Scanning

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Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions

Culos, A., Tsai, A. S., Stanley, N., Becker, M., Ghaemi, M. S., McIlwain, D. R., Fallahzadeh, R., Tanada, A., Nassar, H., Espinosa, C. A., et al. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-020-00232-8 · Cited by 77 · see citing works

Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions

Chen, S., Yu, J., Chamouni, S., Wang, Y., & Li, Y. (2024) · BMC Medicine · doi:10.1186/s12916-024-03566-x · Cited by 73 · see citing works

Machine learning of materials design and state prediction for lithium ion batteries

Mao, J., Miao, J., Lü, Y., & Tong, Z. (2021) · Chinese Journal of Chemical Engineering · doi:10.1016/j.cjche.2021.04.009 · Cited by 62 · see citing works

Serverless Prediction of Peptide Properties with Recurrent Neural Networks

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Processing, Characteristics and Composition of Umqombothi (a South African Traditional Beer)

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Computer Audition for Healthcare: Opportunities and Challenges

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A modeling method for the development of a bioprocess to optimally produce umqombothi (a South African traditional beer)

Hlangwani, E., Doorsamy, W., Adebo, J. A., Fajimi, L. I., & Adebo, O. A. (2021) · Scientific Reports · doi:10.1038/s41598-021-00097-w · Cited by 34 · see citing works

Artificial intelligence for precision medicine in autoimmune liver disease

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Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions

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New Therapeutic Targets in Autoimmune Cholangiopathies

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‘If You’re Going to Trust the Machine, Then That Trust Has Got to Be Based on Something’:

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Deep learning model for classification and bioactivity prediction of essential oil-producing plants from Egypt

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Best practices for machine learning in antibody discovery and development

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Expert-enhanced machine learning for cardiac arrhythmia classification

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Are bibliometric measures consistent with scientists’ perceptions? The case of interdisciplinarity in research

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Machine learning in biological research: key algorithms, applications, and future directions

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Artificial Intelligence in the Management of Women with Endometriosis and Adenomyosis: Can Machines Ever Be Worse Than Humans?

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The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics – an Assessment of the State of Play

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Understanding the phytotoxic effects of organic contaminants on rice through predictive modeling with molecular descriptors: A data-driven analysis

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Filtered partial differential equations: a robust surrogate constraint in physics-informed deep learning framework

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DOME: recommendations for supervised machine learning validation in biology

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Artificial Intelligence in Imaging in the First Trimester of Pregnancy: A Systematic Review

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How to Design a Relevant Corpus for Sleepiness Detection Through Voice?

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The Optimisation of Bitter Gourd-Grape Beverage Fermentation Using a Consolidated Response Surface Methodology (RSM) and Artificial Neural Network (ANN) Approach

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Good machine learning practices: Learnings from the modern pharmaceutical discovery enterprise

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Discovering AI adoption patterns from big academic graph data

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An approachable, flexible and practical machine learning workshop for biologists

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The evolution of knowledge on genes associated with human diseases

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Evolutionary Deep Learning for Sequential Data Processing in Music Education

Lin, J. (2024) · Informatica · doi:10.31449/inf.v48i8.5444 · Cited by 5 · see citing works

Reproducibility and Environmental Efficiency of Metabolomics Cancer Modeling

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At the Crossroads Between Psychiatry and Machine Learning: Insights Into Paradigms and Challenges for Clinical Applicability

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Rates and predictors of data and code sharing in the medical and health sciences: A systematic review with meta-analysis of individual participant dataPreprint

Hamilton, D. G., Hong, K., Fraser, H. S., Rowhani-Farid, A., Fidler, F. M., & Page, M. J. (2023) · medRxiv · doi:10.1101/2023.03.22.23287607 · Cited by 5 · see citing works

Literature review: Current trends and future prospects of digital vaccine supply chain support technology

Ran, W., Li, Z., Xue, Y., & Dandan, H. (2025) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2025.2553454 · Cited by 4 · see citing works

Explainability methods for machine learning systems for multimodal medical datasets

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Ontology-Driven Knowledge Sharing in Alzheimer’s Disease Research

Lazarova, S., Petrova‐Antonova, D., & Kunchev, T. (2023) · Information · doi:10.3390/info14030188 · Cited by 4 · see citing works

Modelling outbreak response impact in human vaccine-preventable diseases: A systematic review of differences in practices between collaboration types before COVID-19

Azam, J. M., Pang, X., Are, E. B., Pulliam, J. R. C., & Ferrari, M. J. (2023) · Epidemics · doi:10.1016/j.epidem.2023.100720 · Cited by 4 · see citing works

Artificial Intelligence in Mental Healthcare

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Empowering scientific discovery with explainable small domain-specific and large language models

Yu, H., Wang, Y., Cheng, T., Yan, Y., Dawson, K. A., Li, S. F. Y., Zheng, Y., & Jin, Y. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11365-w · Cited by 3 · see citing works

Biological data studies, scale-up the potential with machine learning

Malinda, R. R. (2023) · European Journal of Human Genetics · doi:10.1038/s41431-023-01361-5 · Cited by 3 · see citing works

Translational Challenges of Biomedical Machine Learning Solutions in Clinical and Laboratory Settings

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Balancing ideals and realities: health care professionals’ perspectives of and attitudes toward digital patient-centered cancer care

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Focusing on Data to Improve Machine Learning-Guided Antibiotic Discovery

Ta, W., Naiberg, R., Yoon, C. H., Pao, S. Y., Tindall, J., Liu, G., & Stokes, J. M. (2026) · Microbial Drug Resistance · doi:10.1177/10766294261431279 · Cited by 1 · see citing works

Artificial intelligence drives the identification and screening of novel antibiotics and antimicrobial peptides

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Cobotic Ultrasound Systems in Obstetric Assessment: A Scoping Review

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Integration of Mechanistic Immunological Knowledge into a Machine Learning Pipeline Increases Predictive PowerPreprint

Culos, A., Tsai, A. S., Stanley, N., Becker, M., Ghaemi, M. S., McIlwain, D. R., Fallahzadeh, R., Tanada, A., Nassar, H., Ganio, E. A., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.26.967232

Models and modelling practices for assessing the impact of outbreak response interventions to human vaccine-preventable diseases (1970-2019) - A systematic reviewPreprint

Azam, J. M., Pang, X., Are, E. B., Pulliam, J. R. C., & Ferrari, M. J. (2022) · medRxiv · doi:10.1101/2022.05.27.22275642

Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine

Villmann, T., Almeida, J. S., John, L., & Vinga, S. (2022) · European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) · doi:10.14428/esann/2022.es2022-3

Good Machine Learning Practices in the Modern Pharmaceutical Discovery EnterprisePreprint

Makarov, V. A., Chabbert, C. D., Koletou, E., Psomopoulos, F. E., Kurbatova, N., Ramírez, S., Nelson, C., Natarajan, P., & Neupane, B. (2023) · doi:10.31219/osf.io/kuz8p

Exploring SLC25A42 as a Radiogenomic Marker from the Perioperative Stage to Chemotherapy in Hepatitis-Related Hepatocellular Carcinoma

Dou, L., Jiang, J., Yao, H., Zhang, B., & Wang, X. (2025) · Cancer Biotherapy and Radiopharmaceuticals · doi:10.1089/cbr.2025.0094

Digital research ecosystem for Ayurveda: A narrative mapping of global, Ayush, and disease-specific databases

Yadav, A., Mahajon, B., Galib, R., & Ravishankar, B. (2026) · International Journal of Ayurveda Research · doi:10.4103/ijar.ijar_390_25

Multidimensional behavioral endpoints in zebrafish: Toward integrative neurotoxicity assessment under environmental stress

Liu, X., Li, C., Yang, Y., Li, L., Zeng, W., Huang, Z., Huang, Y., & Hong, Y. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106666

Artificial intelligence and machine learning in hepatology: Revolutionizing diagnosis and treatment

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Toward explainable and adaptive artificial intelligence systems for antimicrobial peptide discovery under resistance pressure

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