Predicting protein structure from primary sequence is one of the ultimate challenges in computational biology. Given the large amount of available sequence data, the analysis of co-evolution, i.e., st

NIAID Data Ecosystem50

Additional file 11 of Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species

蛋白质相互作用

共进化分析

Mann-Whitney tests for difference in precision between MI and other methods for N eff /L > 1.6 and FPR < 0.1 % in the HisKA-RR sub-alignments, with contacts defined from experimental studies. (C

DataCite Commons2024-12-13 更新30

Additional file 1 of Inferring RNA sequence preferences for poorly studied RNA-binding proteins based on co-evolution

RNA-蛋白质相互作用

共进化分析

Supplementary Data. The excel document contains the Supplementary Data about the performances of different methods on InVitro, InVivoRay and InVivoAURA datasets, as well as the composition of each dat

NIAID Data Ecosystem20

Additional file 3 of Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species

资源简介：

Additional file 3 of Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species

资源简介：

相关数据集