news
Capturing the computational abilities of real neurons
A new neural network computational model has been developed, which more closely reflects the abilities of real neurons and could advance AI progress.
List view / Grid view
Informatics
news
AI tool identifies high-risk subtype of endometrial cancer
The tool identified patients with high-risk disease, which normally goes unrecognised by traditional diagnostics.
article
Part one: what can scientists do with LLMs today?
Recently there have been a flurry of announcements from AI-led biotechs around the potential of Large Language Models (LLM) in early drug discovery. In the first of a three-part series, Dr Raminderpal Singh explores what LLMs are, how early stage biotechs can take advantage of them, and what challenges they…
article
Kickstarting the use of AI for biotechs: part three
Traditional wet lab scientists working on target discovery, drug identification and drug optimisation have an opportunity to catch up with their AI-enabled peers – but why should they, and how? In this article – the third of a three-part series – Dr Raminderpal Singh touches on the decisions that need…
article
New algorithm forms atlas of histomorphological phenotypes
The algorithm can accurately diagnose cases of lung adenocarcinoma, determining structural features that are statistically most significant for assessing disease severity and likelihood of tumour recurrence.
article
Kickstarting the use of AI for biotechs: part two
Traditional wet lab scientists working on target discovery, drug identification and drug optimisation have an opportunity to catch up with their AI-enabled peers – but why should they, and how? In this article – the second of a three-part series – Dr Raminderpal Singh touches on methods that are being…
article
Kickstarting the use of AI for biotechs: part one
Traditional wet lab scientists working on target discovery, drug identification and drug optimisation have an opportunity to catch-up with their AI-enabled peers – but why should they, and how? In this article – the first of a three-part series – Dr Raminderpal Singh seeks to demystify the topic by outlining…
article
Using AI to predict metastatic behaviour of NSCLC
Dr Richard Cote and Dr Ramaswamy Govindan of the Washington University School of Medicine elucidate how AI, particularly deep learning networks, could identify histopathologic features in non-small cell lung cancer, and impact the treatment approach for early-stage patients.
news
New algorithm identifies high-risk precancerous lesions
Researchers have developed an algorithm which could improve diagnostics of ovarian high-grade serous carcinoma.
article
Scalable precision design targeting complex product profiles
We had the privilege of speaking to Dr Víctor Sebastián Pérez, Associate Director of Computational Drug Design, following his presentation at ELRIG UK 2023. He shares his insights into how Exscientia is using AI to design drug candidates for cancer treatment.
news
Mapping functional states of oncoproteins with AI
Researchers have developed a computational analysis tool which will improve patient stratification and enable personalised medicine.
news
A new machine learning tool identifies drugs to minimise fibrosis
The computer model enables a better understanding of how drugs affect fibroblasts and finds a promising candidate to prevent heart scarring.
news
Advantages of using cfDNA sequencing for early detection of GDM
A deep learning model developed using circulating cell-free DNA outperformed traditional screening methods for gestational diabetes mellitus.
news
Novel prediction tool accurately determines disease stage
A new learning-based framework enables patients and caregivers to predict the timing of any of the five clinical groups of AD development.
whitepaper
Whitepaper: Targeting kinases in the innate immune response
The guide provides examples of how Transcreener allowed rapid assay development to enable screening for kinases in innate immune pathways.
