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
Messenger RNA Subcellular Localization via Hybrid Feature Extraction and Ensemble Learning

book-chapter Full Text OpenAlex

Large-scale protein clustering in the age of deep learning

review Full Text OpenAlex

A general substitution matrix for structural phylogenetics.

article Full Text OpenAlex

Hierarchical Extended Linkage Method (HELM)’s Deep Dive into Hybrid Clustering Strategies

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

article Full Text OpenAlex

Trainable subnetworks reveal insights into structure knowledge organization in protein language models

preprint Full Text OpenAlex

A Machine Learning-Driven, Probability-Based Approach to Enzyme Catalysis

article Full Text OpenAlex

Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER

article Full Text OpenAlex

MULAN: Multimodal Protein Language Model for Sequence and Structure Encoding

article Full Text OpenAlex

Bioinformatic discovery of type 11 secretion system (T11SS) cargo across the Proteobacteria

article Full Text OpenAlex

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

article Full Text OpenAlex 32427 FWCI2182.685

ColabFold: making protein folding accessible to all

article Full Text OpenAlex 7130 FWCI708.774

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

article Full Text OpenAlex 6429 FWCI442.639

UniProt: the Universal Protein Knowledgebase in 2023

article Full Text OpenAlex 4540 FWCI463.525

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

article Full Text OpenAlex 2783 FWCI172.782

Highly accurate protein structure prediction for the human proteome

article Full Text OpenAlex 2627 FWCI185.851

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

article Full Text OpenAlex 2285 FWCI397.007

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

article Full Text OpenAlex 2028 FWCI135.363

InterPro in 2022

article Full Text OpenAlex 1889 FWCI190.729

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

article Full Text OpenAlex 1849 FWCI185.865