PanMAN data structures compress pangenomes massively, encode evolutionary histories, and enable scalable analysis of millions of genomes.
This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
A new artificial intelligence model could help design antibodies that better protect the body against viruses and disease. The AI model, known as ImmunoMatch, can predict and identify correct protein ...
Multimodal Capability: Interprets protein sequences and generates textual insights. LLaVA-Based Architecture: Integrates a resampling mechanism for improved protein-to-text mapping. Curated Training ...
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The reliability of multiple sequence alignment (MSA) results directly determines the credibility of the conclusions drawn from biological research. However, MSA is inherently an NP-hard problem, ...
Recently, a range of effective methods have been developed for predicting protein-protein interactions (PPIs). Among them, the methods based on data derived from protein sequences and structures have ...
Laura holds a Master's in Experimental Neuroscience and a Bachelor's in Biology from Imperial College London. Her areas of expertise include health, medicine, psychology, and neuroscience. Laura holds ...
Abstract: The expansion of protein sequence research has emerged as a prominent area of focus in the field of bioinformatics. The growing need for accurate evolutionary relationships has spurred ...
In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...
Our Atomic Composition Protein Calculator provides a precise elemental breakdown of your protein sequence. By simply inputting a sequence, this tool calculates the exact number of Carbon (C), Hydrogen ...
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