All Bioinformatics articles
-
NewsInsilico Medicine launches AI drug discovery benchmarking platform
Insilico Medicine has unveiled a benchmarking platform designed to assess whether AI models can perform genuine drug discovery tasks, using decontaminated real-world datasets and proprietary validated programmes to move beyond inflated benchmark scores.
-
NewsFullscope-seq maps transcript isoforms with spatial single-cell resolution
Researchers have developed Fullscope-seq, a long-read spatial transcriptomics platform that maps alternative transcript isoforms within intact tissues at single-cell resolution – opening new possibilities for target identification and precision biomarker discovery.
-
ArticleAI’s promise and practical limits in drug discovery
From ChatGPT to AI agents and world models, where is AI really heading in drug discovery? Dr Raminderpal Singh explains what researchers should focus on now.
-
News3D genome reorganisation identified as Alzheimer’s disease molecular hallmark
An international study combining single-cell genomics, spatial transcriptomics and artificial intelligence has identified large-scale changes in three-dimensional genome organisation in Alzheimer’s-affected brain cells, establishing chromatin architecture as a previously overlooked component of the disease’s molecular pathology and a potential framework for future therapeutic targeting.
-
NewsInsilico Medicine nominates ISM9528 non-opioid chronic pain candidate using AI
Insilico Medicine has nominated ISM9528, an orally available, brain-penetrant non-opioid candidate targeting a previously unrecognised pain mechanism, as its 31st AI-generated preclinical compound since 2021, with efficacy exceeding morphine in some preclinical models.
-
NewsSpatial map reveals hidden complexity of bladder cancer tumours
Researchers at MD Anderson Cancer Center have used spatial transcriptomics to chart the internal architecture of muscle-invasive bladder cancer, revealing that luminal and basal cancer cell programmes coexist within single tumours – a finding with significant implications for treatment stratification.
-
ArticleAI’s real value in drug discovery may be choosing the right experiment
AI is becoming more capable, but its value still depends on the data, questions and decisions behind it. Where is it genuinely improving drug discovery and where do the limitations remain?
-
NewsAccessible multiplex imaging workflow advances spatial liver disease research
A new multiplex immunofluorescence workflow using standard laboratory equipment and open-source software enables detailed spatial analysis of liver tissue, organoids and organ-on-a-chip models, lowering barriers to advanced spatial biology in hepatology research.
-
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
Discover how spatial biology is revealing disease mechanisms with implications for biomarkers, 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.