12 papers · ranked by Valyu relevance
Zhaohan Meng, Zhen Bai, Ke Yuan, Jiangning Song + 10 more
Protein-ligand binding governs enzymatic catalysis, metabolic homeostasis, and therapeutic modulation. Thus, the accurate prediction of these interactions underpins modern rational drug discovery. However, existing deep-learning frameworks largely operate as black-box predictors that fail to resolve the individual…
Aniruddh Goteti, Alexandra Vasilyeva, Çağlar Bozkurt
Predicting ligand binding sites is central to computational biology and drug discovery. Existing machine learning approaches either use protein sequence, structure, or both. While structure-based deep learning models typically outperform sequence-based methods, they often require high computational cost or…
Damiano Buratto, Wanding Wang, Xinyi Zhang, Qiujie Zhu + 4 more
The increasing availability of computational power is opening unprecedented opportunities in computational biology and drug design. Computer simulations based on physical models can now reproduce or replace critical biophysical experiments such as binding affinity evaluations in the drug screening process. Here we…
Keyu Xu, Zeyuan Di, Jianquan Zhao, Haicang Zhang + 1 more
Proteins are essential biological macromolecules that play a crucial role in living organisms. Protein-protein interactions, which govern various biological processes such as signal transduction, cell metabolism, and cell growth, are key aspect of protein function. The strength of these interactions, characterized by…
Matthieu Vilain, Stéphane Aris-Brosou
The ever-growing amount of available biological data leads modern analysis to be performed on large datasets. Unfortunately, bioinformatics tools for preprocessing and analyzing data are not always designed to treat such large amounts of data efficiently. Notably, this is the case when encoding DNA and RNA sequences…
Anushriya Subedy, Siddharth Bhadra-Lobo, Guillaume Lamoureux
Predicting antibody-antigen binding affinity is critical for therapeutic development, but machine learning-based approaches to the problem are typically hampered by the small amount of available structural and affinity data. We introduce SE3Bind, an SE(3)-equivariant architecture trained on two related tasks…
Andre Watson
De novo peptide design methods traditionally couple generation to 3D structure prediction, limiting throughput to seconds or hours per candidate. Here we present LigandForge, a discrete diffusion model that generates binding peptide sequences in a single forward pass from receptor pocket geometry alone — no structure…
Alexander Alsalihi, Robert M. Flight, Hunter N. B. Moseley
The recount3 online resource provides tens of thousands of uniformly processed RNA-seq samples across human and mouse from major sequencing repositories like the Sequence Read Archive. While access to these datasets has traditionally been centered in the R/Bioconductor ecosystem, the growing prominence of Python in…
Steven B. Wells, Hamna Shahnawaz, Joanne L. Jones
dreampy is a Python implementation of the R dreamlet framework for pseudobulk differential expression analysis of single-cell RNA-seq data. dreamlet combines voom precision-weighted linear mixed models with empirical Bayes moderation to handle batch effects, repeated measures, and other hierarchical structure in…
Pritam Kumar Panda
Protein–ligand interaction diagrams are a routine part of structural and medicinal chemistry, but the tools that produce them tend to force a choice: comprehensive detection with tabular output, publication-quality figures behind a licence, or a scripting environment that assumes expertise. PandaMap (Protein AND ligAnd…
JF Mulvey
pylimma is a faithful Python port of limma, intended to bring one of the most widely used tools for differential expression analysis to the developing Python ecosystem for transcriptomics and proteomics. We validated pylimma against the existing R implementation through 227 function-level comparisons and across six…
Shuke Xiao, Mengjie Wang, Thomas G. Martin, Barry Scott + 27 more
Most mammals consume small and frequent meals. By contrast, pythons are ambush predators that exhibit extreme feeding and fasting patterns and provide a unique model for uncovering molecular mediators of the postprandial response^1–3^. Using untargeted metabolomics, here we show that circulating levels of the…