AIMC Topic: Databases, Protein

Clear Filters Showing 231 to 240 of 766 articles

DBP-GAPred: An intelligent method for prediction of DNA-binding proteins types by enhanced evolutionary profile features with ensemble learning.

Journal of bioinformatics and computational biology
DNA-binding proteins (DBPs) perform an influential role in diverse biological activities like DNA replication, slicing, repair, and transcription. Some DBPs are indispensable for understanding many types of human cancers (i.e. lung, breast, and liver...

Accurate prediction of protein structures and interactions using a three-track neural network.

Science (New York, N.Y.)
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track ...

Highly accurate protein structure prediction with AlphaFold.

Nature
Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined, but this r...

Deep learning for peptide identification from metaproteomics datasets.

Journal of proteomics
Metaproteomics is becoming widely used in microbiome research for gaining insights into the functional state of the microbial community. Current metaproteomics studies are generally based on high-throughput tandem mass spectrometry (MS/MS) coupled wi...

A Multitask Deep-Learning Method for Predicting Membrane Associations and Secondary Structures of Proteins.

Journal of proteome research
Prediction of residue-level structural attributes and protein-level structural classes helps model protein tertiary structures and understand protein functions. Existing methods are either specialized on only one class of proteins or developed to pre...

Machine learning differentiates enzymatic and non-enzymatic metals in proteins.

Nature communications
Metalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate b...

MILAMP: Multiple Instance Prediction of Amyloid Proteins.

IEEE/ACM transactions on computational biology and bioinformatics
Amyloid proteins are implicated in several diseases such as Parkinson's, Alzheimer's, prion diseases, etc. In order to characterize the amyloidogenicity of a given protein, it is important to locate the amyloid forming hotspot regions within the prot...

Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.

International journal of molecular sciences
The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques tha...

Protein Structure Prediction: Conventional and Deep Learning Perspectives.

The protein journal
Protein structure prediction is a way to bridge the sequence-structure gap, one of the main challenges in computational biology and chemistry. Predicting any protein's accurate structure is of paramount importance for the scientific community, as the...

Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides.

International journal of molecular sciences
Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop ...