AIMC Topic: Proteins

Clear Filters Showing 1931 to 1940 of 2080 articles

Analysis of several key factors influencing deep learning-based inter-residue contact prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Deep learning has become the dominant technology for protein contact prediction. However, the factors that affect the performance of deep learning in contact prediction have not been systematically investigated.

Learning from the ligand: using ligand-based features to improve binding affinity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Machine learning scoring functions for protein-ligand binding affinity prediction have been found to consistently outperform classical scoring functions. Structure-based scoring functions for universal affinity prediction typically use fe...

PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins.

Bioinformatics (Oxford, England)
MOTIVATION: Gram-positive bacteria have developed secretion systems to transport proteins across their cell wall, a process that plays an important role during host infection. These secretion mechanisms have also been harnessed for therapeutic purpos...

DEEPCON: protein contact prediction using dilated convolutional neural networks with dropout.

Bioinformatics (Oxford, England)
MOTIVATION: Exciting new opportunities have arisen to solve the protein contact prediction problem from the progress in neural networks and the availability of a large number of homologous sequences through high-throughput sequencing. In this work, w...

DeepGOPlus: improved protein function prediction from sequence.

Bioinformatics (Oxford, England)
MOTIVATION: Protein function prediction is one of the major tasks of bioinformatics that can help in wide range of biological problems such as understanding disease mechanisms or finding drug targets. Many methods are available for predicting protein...

Artificial intelligence-based multi-objective optimization protocol for protein structure refinement.

Bioinformatics (Oxford, England)
MOTIVATION: Protein structure refinement is an important step of protein structure prediction. Existing approaches have generally used a single scoring function combined with Monte Carlo method or Molecular Dynamics algorithm. The one-dimension optim...

The neXtProt knowledgebase in 2020: data, tools and usability improvements.

Nucleic acids research
The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describ...

OCCAM: prediction of small ORFs in bacterial genomes by means of a target-decoy database approach and machine learning techniques.

Database : the journal of biological databases and curation
Small open reading frames (ORFs) have been systematically disregarded by automatic genome annotation. The difficulty in finding patterns in tiny sequences is the main reason that makes small ORFs to be overlooked by computational procedures. However,...

Using Reduced Amino Acid Alphabet and Biological Properties to Analyze and Predict Animal Neurotoxin Protein.

Current drug metabolism
AIMS: Because of the high affinity of these animal neurotoxin proteins for some special target site, they were usually used as pharmacological tools and therapeutic agents in medicine to gain deep insights into the function of the nervous system.