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AniAMPpred: artificial intelligence guided discovery of novel antimicrobial peptides in animal kingdom.
Briefings in bioinformatics
Nov 5, 2021
With advancements in genomics, there has been substantial reduction in the cost and time of genome sequencing and has resulted in lot of data in genome databases. Antimicrobial host defense proteins provide protection against invading microbes. But c...
Integrative machine learning framework for the identification of cell-specific enhancers from the human genome.
Briefings in bioinformatics
Nov 5, 2021
Enhancers are deoxyribonucleic acid (DNA) fragments which when bound by transcription factors enhance the transcription of related genes. Due to its sporadic distribution and similar fractions, identification of enhancers from the human genome seems ...
Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution.
Briefings in bioinformatics
Nov 5, 2021
Major histocompatibility complex (MHC) possesses important research value in the treatment of complex human diseases. A plethora of computational tools has been developed to predict MHC class I binders. Here, we comprehensively reviewed 27 up-to-date...
PSSP-MVIRT: peptide secondary structure prediction based on a multi-view deep learning architecture.
Briefings in bioinformatics
Nov 5, 2021
The prediction of peptide secondary structures is fundamentally important to reveal the functional mechanisms of peptides with potential applications as therapeutic molecules. In this study, we propose a multi-view deep learning method named Peptide ...
An artificial neural network model based on DNA damage response genes to predict outcomes of lower-grade glioma patients.
Briefings in bioinformatics
Nov 5, 2021
Although the prognosis of lower-grade glioma (LGG) patients is better than others, outcomes are highly heterogeneous. Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status can identify patient subsets with different prognosis. However,...
Multi-view Multichannel Attention Graph Convolutional Network for miRNA-disease association prediction.
Briefings in bioinformatics
Nov 5, 2021
MOTIVATION: In recent years, a growing number of studies have proved that microRNAs (miRNAs) play significant roles in the development of human complex diseases. Discovering the associations between miRNAs and diseases has become an important part of...
Exploring the Scoring Function Space.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
In the analysis of protein-ligand interactions, two abstractions have been widely employed to build a systematic approach to analyze these complexes: protein and chemical spaces. The pioneering idea of the protein space dates back to 1970, and the ch...
Machine Learning to Predict Binding Affinity.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Recent progress in the development of scientific libraries with machine-learning techniques paved the way for the implementation of integrated computational tools to predict ligand-binding affinity. The prediction of binding affinity uses the atomic ...
Building Machine-Learning Scoring Functions for Structure-Based Prediction of Intermolecular Binding Affinity.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Molecular docking enables large-scale prediction of whether and how small molecules bind to a macromolecular target. Machine-learning scoring functions are particularly well suited to predict the strength of this interaction. Here we describe how to ...
Design of Knowledge Bases for Plant Gene Regulatory Networks.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2017
Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary ...
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Knowledge Bases
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Gene Regulatory Networks
Databases, Genetic
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