AIMC Topic: DNA-Binding Proteins

Clear Filters Showing 51 to 60 of 104 articles

Use Chou's 5-Step Rule to Predict DNA-Binding Proteins with Evolutionary Information.

BioMed research international Jul 27, 2020
The knowledge of DNA-binding proteins would help to understand the functions of proteins better in cellular biological processes. Research on the prediction of DNA-binding proteins can promote the research of drug proteins and computer acidified drug...
Computational Biology Support Vector Machine Evolution, Molecular Databases, Protein DNA-Binding Proteins
View on PubMed DOI

Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning.

Gastroenterology Jun 17, 2020
BACKGROUND & AIMS: Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and le...
Deep Learning Cohort Studies ROC Curve Brain Neoplasms Male Middle Aged MutL Protein Homolog 1 Predictive Value of Tests Mismatch Repair Endonuclease PMS2 Neoplastic Syndromes, Hereditary Microsatellite Instability MutS Homolog 2 Protein DNA-Binding Proteins Humans Adult Female Colorectal Neoplasms
View on PubMed DOI

PredDBP-Stack: Prediction of DNA-Binding Proteins from HMM Profiles using a Stacked Ensemble Method.

BioMed research international Apr 13, 2020
DNA-binding proteins (DBPs) play vital roles in all aspects of genetic activities. However, the identification of DBPs by using wet-lab experimental approaches is often time-consuming and laborious. In this study, we develop a novel computational met...
DNA-Binding Proteins Software Support Vector Machine Databases, Protein
View on PubMed DOI

HMMPred: Accurate Prediction of DNA-Binding Proteins Based on HMM Profiles and XGBoost Feature Selection.

Computational and mathematical methods in medicine Mar 28, 2020
Prediction of DNA-binding proteins (DBPs) has become a popular research topic in protein science due to its crucial role in all aspects of biological activities. Even though considerable efforts have been devoted to developing powerful computational ...
Amino Acid Sequence Markov Chains Databases, Protein Amino Acids DNA-Binding Proteins Humans Machine Learning Algorithms ROC Curve Computational Biology Support Vector Machine
View on PubMed DOI

Identification of Methylated Gene Biomarkers in Patients with Alzheimer's Disease Based on Machine Learning.

BioMed research international Mar 26, 2020
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder and characterized by the cognitive impairments. It is essential to identify potential gene biomarkers for AD pathology.
Microfilament Proteins Cyclin-Dependent Kinase Inhibitor p57 Protein Tyrosine Phosphatases Patients Gene Expression Regulation, Neoplastic Peptide Hydrolases Transcription Factors Mitochondrial Proteins DNA Methylation Humans Genetic Markers Machine Learning Carrier Proteins Alzheimer Disease DNA-Binding Proteins
View on PubMed DOI

Deep learning approaches for sleep disorder prediction in an asthma cohort.

The Journal of asthma : official journal of the Association for the Care of Asthma Mar 18, 2020
OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore, sleep disturbance may lead to fatigue and lower productivity. This study examined 1 million samples included in the Taiwan National Health Insurance ...
Humans Adult Asthma Male Middle Aged Artificial Intelligence Female Young Adult Predictive Value of Tests DNA-Binding Proteins Sleep Wake Disorders Child, Preschool Infant Child Deep Learning Nerve Tissue Proteins Adolescent
View on PubMed DOI

iProDNA-CapsNet: identifying protein-DNA binding residues using capsule neural networks.

BMC bioinformatics Dec 27, 2019
BACKGROUND: Since protein-DNA interactions are highly essential to diverse biological events, accurately positioning the location of the DNA-binding residues is necessary. This biological issue, however, is currently a challenging task in the age of ...
Position-Specific Scoring Matrices Amino Acids DNA-Binding Proteins Humans Amino Acid Sequence Neural Networks, Computer Reproducibility of Results Software ROC Curve DNA Algorithms
View on PubMed DOI

An improved deep learning method for predicting DNA-binding proteins based on contextual features in amino acid sequences.

PloS one Nov 14, 2019
As the number of known proteins has expanded, how to accurately identify DNA binding proteins has become a significant biological challenge. At present, various computational methods have been proposed to recognize DNA-binding proteins from only amin...
Memory, Long-Term Deep Learning Neural Networks, Computer DNA-Binding Proteins Algorithms Reproducibility of Results Amino Acid Sequence
View on PubMed DOI

SDBP-Pred: Prediction of single-stranded and double-stranded DNA-binding proteins by extending consensus sequence and K-segmentation strategies into PSSM.

Analytical biochemistry Nov 3, 2019
Identification of DNA-binding proteins (DNA-BPs) is a hot issue in protein science due to its key role in various biological processes. These processes are highly concerned with DNA-binding protein types. DNA-BPs are classified into single-stranded D...
Support Vector Machine Databases, Protein DNA-Binding Proteins Amino Acid Sequence Computational Biology Datasets as Topic Consensus Sequence
View on PubMed DOI

FKRR-MVSF: A Fuzzy Kernel Ridge Regression Model for Identifying DNA-Binding Proteins by Multi-View Sequence Features via Chou's Five-Step Rule.

International journal of molecular sciences Aug 26, 2019
DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the detection methods of DNA-binding proteins includes yeast one-hybrid methods, bacterial singles and X-ray crystallography methods and others, but these met...
Machine Learning Sensitivity and Specificity Regression Analysis ROC Curve Reproducibility of Results DNA-Binding Proteins Computational Biology
View on PubMed DOI
Popular Topics
Recent Journals