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
Integrating 16S rRNA identification for a promising epitope-based vaccine strategy against Bacillus licheniformis infections causing foodborne illness

article Full Text OpenAlex

Hidden in protein sequences: Predicting cryptic binding sites

article Full Text OpenAlex

GlyTrait: A Versatile Bioinformatics Tool for Glycomics Analysis

article Full Text OpenAlex

Segment Any Cell: A SAM-Based Auto-Prompting Fine-Tuning Framework for Nuclei Segmentation

article Full Text OpenAlex

CNNCaps-DBP: Leveraging protein language models with attention-augmented convolution for DNA-binding protein prediction

article Full Text OpenAlex

EAP-LSTM: A Bi-LSTM-based Deep Learning Framework for Quantitatively Predicting Enhancer Activity in Drosophila and Human Cell Lines

article Full Text OpenAlex

Identification and evaluation of phytochemicals as potential inhibitors for lung cancer targeting EGFR exon-19 deletion: A comprehensive study utilizing computational biology approaches

article Full Text OpenAlex

ProAttUnet: Advancing protein secondary structure prediction with deep learning via U-Net dual-pathway feature fusion and ESM2 pretrained protein language model

article Full Text OpenAlex

Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification

article Full Text OpenAlex

Explainable Deep Multilevel Attention Learning for Predicting Protein Carbonylation Sites

article Full Text OpenAlex

近5年高被引文献
ColabFold: making protein folding accessible to all

article Full Text OpenAlex 8875 FWCI1092.4849154

UniProt: the Universal Protein Knowledgebase in 2023

article Full Text OpenAlex 6204 FWCI771.02827475

Using Embeddings to Improve Named Entity Recognition Classification with Graphs

preprint Full Text OpenAlex 5332 FWCI780.88198805

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

article Full Text OpenAlex 3858 FWCI717.24478468

InterPro in 2022

article Full Text OpenAlex 2389 FWCI308.53437906

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

article Full Text OpenAlex 2358 FWCI298.56577726

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

article Full Text OpenAlex 2093 FWCI257.4606785

Fast and accurate protein structure search with Foldseek

article Full Text OpenAlex 1931 FWCI354.07346736

Robust deep learning–based protein sequence design using ProteinMPNN

article Full Text OpenAlex 1443 FWCI174.63513518

DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks

preprint Full Text OpenAlex 1313 FWCI0