Genetics

High-Order Convolutional Neural Network Architecture for Predicting DNA-Protein Binding Sites.

Although Deep learning algorithms have outperformed conventional methods in predicting the sequence specificities of DNA-protein binding, they lack to consider the dependencies among nucleotides and the diverse binding lengths for different transcription factors (TFs). To address the above two limitations simultaneously, in this paper, we propose a high-order convolutional neural network architect...

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind.

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this stud...

A survey of recently emerged genome-wide computational enhancer predictor tools.

The race for the discovery of enhancers at a genome-wide scale has been on since the commencement of next generation sequencing decades after the disc...

ANTENNA, a Multi-Rank, Multi-Layered Recommender System for Inferring Reliable Drug-Gene-Disease Associations: Repurposing Diazoxide as a Targeted Anti-Cancer Therapy.

Existing drug discovery processes follow a reductionist model of "one-drug-one-gene-one-disease," which is inadequate to tackle complex diseases invol...

Computational Prediction of Sigma-54 Promoters in Bacterial Genomes by Integrating Motif Finding and Machine Learning Strategies.

Sigma factor, as a unit of RNA polymerase holoenzyme, is a critical factor in the process of gene transcriptional regulation. It recognizes the specif...

Chromosome-wide gene dosage rebalance may benefit tumor progression.

The high-risk of tumor initiation in patients with Turner syndrome (TS) characterized by X chromosome monosomy in women has been well established and ...

iRSpot-PDI: Identification of recombination spots by incorporating dinucleotide property diversity information into Chou's pseudo components.

Recombination spot identification plays an important role in revealing genome evolution and developing DNA function study. Although some computational...

Machine Learning of Partial Charges Derived from High-Quality Quantum-Mechanical Calculations.

Parametrization of small organic molecules for classical molecular dynamics simulations is not trivial. The vastness of the chemical space makes appro...

Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.

Autism spectrum disorder (ASD) is a neuropsychiatric disorder with strong evidence of genetic contribution, and increased research efforts have result...

Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning.

Thrombin is a key component for chemotherapeutic and antithrombotic therapy development. As the physiologic and pathologic roles of the light chain st...

Obesity as an independent predictive factor for pathologic complete response after neoadjuvant chemoradiation in rectal cancer.

PURPOSE: The predictive role of obesity on pathologic complete response (pCR) after neoadjuvant chemoradiation (nCRT) in rectal cancer remains controv...

Genes sharing the protein family domain decrease the performance of classification with RNA-seq genomic signatures.

BACKGROUND: The experience with running various types of classification on the CAMDA neuroblastoma dataset have led us to the conclusion that the resu...

Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus.

Although Hi-C technology is one of the most popular tools for studying 3D genome organization, due to sequencing cost, the resolution of most Hi-C dat...

Automated detection of preserved photoreceptor on optical coherence tomography in choroideremia based on machine learning.

Optical coherence tomography (OCT) can demonstrate early deterioration of the photoreceptor integrity caused by inherited retinal degeneration disease...

Identifying neuropsychiatric disorders using unsupervised clustering methods: Data and code.

This article provides data for five different neuropsychiatric disorders-Attention Deficit Hyperactivity Disorder, Alzheimer's Disease, Autism Spectru...

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder.

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large v...

Interaction of Vitamin E Intake and Pro12Ala Polymorphism of PPARG with Adiponectin Levels.

BACKGROUND/AIM: One of the beneficial effects associated with vitamin E intake is the enhancement of peroxisome proliferator-activated receptor gamma ...

Machine Learning on a Genome-wide Association Study to Predict Late Genitourinary Toxicity After Prostate Radiation Therapy.

PURPOSE: Late genitourinary (GU) toxicity after radiation therapy limits the quality of life of prostate cancer survivors; however, efforts to explain...

Functional Categorization of Disease Genes Based on Spectral Graph Theory and Integrated Biological Knowledge.

Interaction of multiple genetic variants is a major challenge in the development of effective treatment strategies for complex disorders. Identifying ...

Risk-Predicting Model for Incident of Essential Hypertension Based on Environmental and Genetic Factors with Support Vector Machine.

Essential hypertension (EH) has become a major chronic disease around the world. To build a risk-predicting model for EH can help to interpose people'...