ArticleJournal of cheminformatics2018
PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions.
Article in Journal of cheminformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed.
- SeqHIVE: a Python package to convert the biological sequences to informative vectors for sequence property predictions.BioData mining · 2026Article
- Integrating molecular generation and fingerprints transferring for single-molecule theranostics targeting endoplasmic reticulum stress.Journal of advanced research · 2026Article
- MLDTA an Ensemble-Driven Multimodal Model with Dynamic Fusion for Drug-Target Affinity Prediction.Interdisciplinary sciences, computational life sciences · 2026Article
- Integrated machine learning and molecular dynamics framework for predicting and elucidating ABCB1 allocrite interactions.Briefings in bioinformatics · 2026Article
- A new high-accuracy QSAR model based on ultra-curated data for predicting thyroid receptor-related endocrine activity.Frontiers in toxicology · 2026Article
- Two-Stage Probability-Enhanced Regression on Property Matrices and LLM Embeddings Enables State-of-the-Art Prediction of Gene Knockdown by Modified siRNAs.International journal of molecular sciences · 2025Article
- Harnessing advanced computational approaches to design novel antimicrobial peptides against intracellular bacterial infections.Bioactive materials · 2025Article
- Machine learning: Python tools for studying biomolecules and drug design.Molecular diversity · 2025Review
- Design, synthesis, and evaluation of triazolo[1,5-a]pyridines as novel and potent α‑glucosidase inhibitors.Scientific reports · 2025Article
- PyPropel: a Python-based tool for efficiently processing and characterising protein data.BMC bioinformatics · 2025Article
- SequenceCraft: machine learning-based resource for exploratory analysis of RNA-cleaving deoxyribozymes.BMC bioinformatics · 2025Article
- Interpretable Artificial Intelligence Decodes the Chemical Structural Essence of Twisted Intramolecular Charge Transfer and Planar Intramolecular Charge Transfer Fluorophores.Research (Washington, D.C.) · 2025Article
- AI-Powered Mining of Highly Customized and Superior ESIPT-Based Fluorescent Probes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- AI-based prediction of protein-ligand binding affinity and discovery of potential natural product inhibitors against ERK2.BMC chemistry · 2024Article
- Introducing enzymatic cleavage features and transfer learning realizes accurate peptide half-life prediction across species and organs.Briefings in bioinformatics · 2024Article
- BiMPADR: A Deep Learning Framework for Predicting Adverse Drug Reactions in New Drugs.Molecules (Basel, Switzerland) · 2024Article
- PhageScanner: a reconfigurable machine learning framework for bacteriophage genomic and metagenomic feature annotation.Frontiers in microbiology · 2024Article
- Article
- From intuition to AI: evolution of small molecule representations in drug discovery.Briefings in bioinformatics · 2023Article
- FormulationAI: a novel web-based platform for drug formulation design driven by artificial intelligence.Briefings in bioinformatics · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundWith the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important. So far, there are no suitable toolkits that can effectively link the chemical and biological space in view of molecular representation. To further explore these complex data, an integrated toolkit for various molecular representation is urgently needed which could be easily integrated with data mining algorithms to start a full data analysis pipeline.
resultsHerein, the python library PyBioMed is presented, which comprises functionalities for online download for various molecular objects by providing different IDs, the pretreatment of molecular structures, the computation of various molecular descriptors for chemicals, proteins, DNAs and their interactions. PyBioMed is a feature-rich and highly customized python library used for the characterization of various complex chemical and biological molecules and interaction samples. The current version of PyBioMed could calculate 775 chemical descriptors and 19 kinds of chemical fingerprints, 9920 protein descriptors based on protein sequences, more than 6000 DNA descriptors from nucleotide sequences, and interaction descriptors from pairwise samples using three different combining strategies. Several examples and five real-life applications were provided to clearly guide the users how to use PyBioMed as an integral part of data analysis projects. By using PyBioMed, users are able to start a full pipelining from getting molecular data, pretreating molecules, molecular representation to constructing machine learning models conveniently.
conclusionPyBioMed provides various user-friendly and highly customized APIs to calculate various features of biological molecules and complex interaction samples conveniently, which aims at building integrated analysis pipelines from data acquisition, data checking, and descriptor calculation to modeling. PyBioMed is freely available at http://projects.scbdd.com/pybiomed.html .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.