All Bioinformatics articles
-
NewsEuropean initiative aims to bring molecular dynamics into mainstream drug discovery
What if the vast amounts of data generated by molecular dynamics simulations could be routinely shared and reused? A new €10 million European initiative aims to do just that, helping researchers gain a deeper understanding of protein behaviour and drug-target interactions.
-
NewsAI-powered $6M project targets new Alzheimer’s treatments
A $6 million NIH-funded collaboration between Indiana University School of Medicine and Luddy School of Informatics aims to deploy AI and machine learning to identify promising Alzheimer’s drug candidates, screening billions of compounds to overcome traditional discovery bottlenecks.
-
ReportContext is everything: how spatial biology is changing our understanding of disease
Researchers can now analyse individual cells in extraordinary detail, yet understanding disease often requires more than studying cells in isolation. This report explores how spatial biology is revealing aspects of disease biology that cannot be captured through individual cells alone, and what that could mean for biomarker discovery, immunotherapy and drug development.
-
ReportAI in Drug Discovery: Progress, Limits and What Comes Next
AI has attracted enormous investment across drug discovery, but major questions still remain around validation, reproducibility and real-world application. In our latest Beyond the Lab report, experts discuss where the technology is starting to influence discovery workflows – and where limitations continue to slow adoption.
-
ArticleFrom chemist to AI agent builder: inside the rise of agentic AI in drug discovery
Dr Raminderpal Singh speaks with Dr Srijit Seal about why specialised AI agents are outperforming general-purpose models in drug discovery and what a new consortium paper shows about their use in practice.
-
NewsParse Biosciences and bit.bio map transcription factor-driven cell identity
Parse Biosciences and bit.bio have formed an alliance to map transcription factor-driven cell identity using single cell sequencing and causal transcriptomics.
-
ArticleMachine learning identifies biological signals linked to emotional hunger
Researchers at Phenomix Sciences are using machine learning and genetic risk scoring to investigate emotional hunger, an obesity phenotype linked to emotional and reward-driven eating behaviours. Dr Timothy O’Connor discusses how the approach could improve patient stratification, obesity research and treatment selection.
-
NewsGinkgo Bioworks launches ADME-One platform for early-stage screening
Ginkgo Bioworks has launched ADME-One, an integrated platform combining high-throughput ADME testing with AI-powered human pharmacokinetic projections.
-
NewsAI platform identifies novel gp130 inhibitor for colorectal cancer
An AI-assisted drug discovery platform using transfer learning has identified a promising gp130 inhibitor for colorectal cancer.
-
NewsAI identifies 23 antiviral candidates for Bundibugyo Ebola strain
US researchers have deployed artificial intelligence and molecular docking software to identify 23 antiviral compounds with potential activity against Bundibugyo Ebolavirus, as the rare strain continues to spread in the Democratic Republic of Congo with a fatality rate approaching 40 percent.
-
ArticleWhy AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
-
ArticleTurning GWAS signals into drug targets with scalable CRISPR
Genome-wide association studies have linked thousands of genetic variants to disease, yet most remain disconnected from drug-relevant biology. Neville Sanjana, Professor at New York University and Core Faculty Member at the New York Genome Center, explains how scalable CRISPR screens systematically link noncoding variants to causal genes and therapeutic targets.
-
NewsOutSee wins Longitude Prize award for ALS target discovery
OutSee has secured a Discovery Award from the Longitude Prize on ALS, providing £100,000 in funding and access to genomic data from 9,000 patients. The company will deploy its AI-driven Nomaly platform to identify novel therapeutic targets for amyotrophic lateral sclerosis over a nine-month research programme.
-
NewsNew RNA sequencing method reveals molecular structures at single-molecule resolution
A*STAR scientists have developed sm-PORE-cupine, a nanopore-based sequencing method that maps individual RNA structures at single-molecule resolution.
-
NewsAI system transforms weak antibiotics into powerful treatments
University of Pennsylvania researchers have developed ApexGO, an AI system that refines imperfect antibiotic candidates through calculated modifications rather than database screening.
-
NewsAI system reduces animal testing in drug discovery by 50 percent
German researchers have developed genESOM, a generative AI system that could reduce animal numbers in preclinical drug testing by 30 to 50 percent.
-
NewsOpenBind launches AI model to accelerate drug discovery
Diamond Light Source has launched OpenBind v1, an open-access AI model and dataset designed to address critical data shortages in drug discovery by providing standardised protein-drug binding measurements at atomic resolution.
-
ArticleThe scale divide: competing strategies in AI drug discovery
Two approaches to AI in preclinical drug discovery are diverging, from multi-thousand GPU systems to models with only a handful of parameters, with early results raising questions about which will deliver.
-
NewsNew immune mapping reveals lung tumour microenvironment dynamics
VIB-VUB researchers have developed a patient-relevant lung adenocarcinoma model combined with SEPARATE-Seq technology to create detailed immune maps distinguishing tissue-infiltrating cells from circulating populations.
-
ArticleFrom leaderboards to lab notebooks: AI designs reach preclinical testing
For years, AI drug discovery has been judged on benchmark performance. Now, a set of studies shows what happens when those designs are made and tested in preclinical settings.