Genetics

Arabic Sentiment Classification Using Convolutional Neural Network and Differential Evolution Algorithm.

In recent years, convolutional neural network (CNN) has attracted considerable attention since its impressive performance in various applications, such as Arabic sentence classification. However, building a powerful CNN for Arabic sentiment classification can be highly complicated and time consuming. In this paper, we address this problem by combining differential evolution (DE) algorithm and CNN,...

Using artificial neural network and multivariate calibration methods for simultaneous spectrophotometric analysis of Emtricitabine and Tenofovir alafenamide fumarate in pharmaceutical formulation of HIV drug.

Spectrophotometric analysis method based on artificial neural network (ANN), partial least squares regression (PLS) and principal component regression (PCR) models was proposed for the simultaneous determination of Emtricitabine (ETB) and Tenofovir alafenamide fumarate (TAF) in human immunodeficiency virus (HIV) drug. An artificial neural network consisting of two, five, and seven layers with 2,3,...

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group for future development of Parkinson's disease (PD...

Deoxyribonuclease I Activity, Cell-Free DNA, and Risk of Liver Cancer in a Prospective Cohort.

BACKGROUND: Circulating cell-free DNA (cfDNA) is a proposed latent biomarker for several cancers, including liver cancer. Deoxyribonucleases (DNases) ...

Unsupervised Learning Approach for Comparing Multiple Transposon Insertion Sequencing Studies.

Transposon insertion sequencing (TIS) is a widely used technique for conducting genome-scale forward genetic screens in bacteria. However, few methods...

Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas.

Based on morphology it is often challenging to distinguish between the many different soft tissue sarcoma subtypes. Moreover, outcome of disease is hi...

Predicting overall survival of patients with hepatocellular carcinoma using a three-category method based on DNA methylation and machine learning.

Hepatocellular carcinoma (HCC) is closely associated with abnormal DNA methylation. In this study, we analyzed 450K methylation chip data from 377 HCC...

Standardizing Automated DNA Assembly: Best Practices, Metrics, and Protocols Using Robots.

The advancement of synthetic biology requires the ability to create new DNA sequences to produce unique behaviors in biological systems. Automation is...

ClinTAD: a tool for copy number variant interpretation in the context of topologically associated domains.

Standard clinical interpretation of DNA copy number variants (CNVs) identified by cytogenomic microarray involves examining protein-coding genes withi...

Automation of the standard DNA differential extraction on the Hamilton AutoLys STAR system: A proof-of-concept study.

For several decades, a common approach for processing sexual assault evidence has been to use the "standard" differential extraction to separate the e...

Statistical outbreak detection by joining medical records and pathogen similarity.

We present a statistical inference model for the detection and characterization of outbreaks of hospital associated infection. The approach combines p...

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans.

State-of-the-art methods assessing pathogenic non-coding variants have mostly been characterized on common disease-associated polymorphisms, yet with ...

A Benchmarking Between Deep Learning, Support Vector Machine and Bayesian Threshold Best Linear Unbiased Prediction for Predicting Ordinal Traits in Plant Breeding.

Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accura...

Prediction of IDH1 Mutation Status in Glioblastoma Using Machine Learning Technique Based on Quantitative Radiomic Data.

OBJECTIVE: Isocitrate dehydrogenase 1 (IDH1) mutation status is an independent favorable prognostic factor for glioblastoma (GBM) and is usually deter...

The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: genomics with bigger data and wider applications.

The sixth International Conference on Intelligent Biology and Medicine (ICIBM) took place in Los Angeles, California, USA on June 10-12, 2018. This co...

Hepatitis Screening and Treatment Campaign in Malaysia-Validation of Low-cost Point of Care Screening Tests and Nucleic Acid Tests for Hepatitis B and C.

BACKGROUND: Two major challenges in implementing budget-constrained Hepatitis screening and treatment campaign in Malaysia are the availability of low...

Predicting drug response of tumors from integrated genomic profiles by deep neural networks.

BACKGROUND: The study of high-throughput genomic profiles from a pharmacogenomics viewpoint has provided unprecedented insights into the oncogenic fea...

Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal .

Nontyphoidal species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susce...

Attribute selection and model evaluation for the maternal and paternal imprinted genes in bovine (Bos Taurus) using supervised machine learning algorithms.

Imprinted genes display biased expression of paternal and maternal alleles in mammals. They are marked through epigenetic process during gametogenesis...

Preparation of albendazole-loaded liposomes by supercritical carbon dioxide processing.

Supercritical fluid (SCF) technology offers a potential green alternative to organic solvent-based methods for drug formulation. Albendazole (ABZ) has...