专题:Machine Learning in Bioinformatics

This cluster of papers focuses on the prediction of protein subcellular localization using various computational methods such as amino acid composition, machine learning algorithms like support vector machines, and the analysis of signal peptides and transmembrane topology. The research aims to improve the accuracy and reliability of predicting the subcellular location of proteins, which has significant implications for understanding protein function and cellular processes.
最新文献
Assessing generative model coverage of protein structures with SHAPES

article Full Text OpenAlex

Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era

review Full Text OpenAlex

How AlphaFold and related models predict protein-peptide complex structures

preprint Full Text OpenAlex

Enhanced RNA secondary structure prediction through integrative deep learning and structural context analysis

article Full Text OpenAlex

Generalized biological foundation model with unified nucleic acid and protein language

article Full Text OpenAlex

A general substitution matrix for structural phylogenetics.

article Full Text OpenAlex

NEFFy: A Versatile Tool for Computing the Number of Effective Sequences

article Full Text OpenAlex

CASP16 protein monomer structure prediction assessment

preprint Full Text OpenAlex

Improving AlphaFold2‐ and AlphaFold3‐Based Protein Complex Structure Prediction With MULTICOM4 in CASP16

article Full Text OpenAlex

Assessment of Protein Complex Predictions in CASP16: Are we making progress?

preprint Full Text OpenAlex

近5年高被引文献
Highly accurate protein structure prediction with AlphaFold

article Full Text OpenAlex 33825 FWCI2186.105

ColabFold: making protein folding accessible to all

article Full Text OpenAlex 7416 FWCI705.623

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

article Full Text OpenAlex 6592 FWCI442.56

UniProt: the Universal Protein Knowledgebase in 2023

article Full Text OpenAlex 4963 FWCI465.985

Sensitive protein alignments at tree-of-life scale using DIAMOND

article Full Text OpenAlex 3089 FWCI173.413

Highly accurate protein structure prediction for the human proteome

article Full Text OpenAlex 2694 FWCI186.255

Evolutionary-scale prediction of atomic-level protein structure with a language model

article Full Text OpenAlex 2646 FWCI401.719

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

article Full Text OpenAlex 2187 FWCI135.508

InterPro in 2022

article Full Text OpenAlex 1979 FWCI189.576

SignalP 6.0 predicts all five types of signal peptides using protein language models

article Full Text OpenAlex 1964 FWCI187.539