Machine learning in drug discovery: a review
This review provides the feasible literature on drug discovery through ML tools and
techniques that are enforced in every phase of drug development to accelerate the research …
techniques that are enforced in every phase of drug development to accelerate the research …
Machine learning meets omics: applications and perspectives
The innovation of biotechnologies has allowed the accumulation of omics data at an
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
Predicting protein structural classes for low-similarity sequences by evaluating different features
Protein structural class could provide important clues for understanding protein fold,
evolution and function. However, it is still a challenging problem to accurately predict protein …
evolution and function. However, it is still a challenging problem to accurately predict protein …
i6mA-Pred: identifying DNA N6-methyladenine sites in the rice genome
Abstract Motivation DNA N6-methyladenine (6mA) is associated with a wide range of
biological processes. Since the distribution of 6mA site in the genome is non-random …
biological processes. Since the distribution of 6mA site in the genome is non-random …
iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators
Motivation Transcription termination is an important regulatory step of gene expression. If
there is no terminator in gene, transcription could not stop, which will result in abnormal …
there is no terminator in gene, transcription could not stop, which will result in abnormal …
Classification and prediction of protein–protein interaction interface using machine learning algorithm
S Das, S Chakrabarti - Scientific reports, 2021 - nature.com
Structural insight of the protein–protein interaction (PPI) interface can provide knowledge
about the kinetics, thermodynamics and molecular functions of the complex while …
about the kinetics, thermodynamics and molecular functions of the complex while …
[PDF][PDF] Identification of hormone binding proteins based on machine learning methods
JX Tan, SH Li, ZM Zhang, CX Chen, W Chen… - Math. Biosci …, 2019 - aimspress.com
The soluble carrier hormone binding protein (HBP) plays an important role in the growth of
human and other animals. HBP can also selectively and non-covalently interact with …
human and other animals. HBP can also selectively and non-covalently interact with …
iEnhancer-5Step: identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding
An enhancer is a short (50–1500bp) region of DNA that plays an important role in gene
expression and the production of RNA and proteins. Genetic variation in enhancers has …
expression and the production of RNA and proteins. Genetic variation in enhancers has …
Predicting protein-protein interactions from matrix-based protein sequence using convolution neural network and feature-selective rotation forest
L Wang, HF Wang, SR Liu, X Yan, KJ Song - Scientific reports, 2019 - nature.com
Protein is an essential component of the living organism. The prediction of protein-protein
interactions (PPIs) has important implications for understanding the behavioral processes of …
interactions (PPIs) has important implications for understanding the behavioral processes of …
Graph-BERT and language model-based framework for protein–protein interaction identification
Identification of protein–protein interactions (PPI) is among the critical problems in the
domain of bioinformatics. Previous studies have utilized different AI-based models for PPI …
domain of bioinformatics. Previous studies have utilized different AI-based models for PPI …