Genetics

The optoelectronic microrobot: A versatile toolbox for micromanipulation.

Microrobotics extends the reach of human-controlled machines to submillimeter dimensions. We introduce a microrobot that relies on optoelectronic tweezers (OET) that is straightforward to manufacture, can take nearly any desirable shape or form, and can be programmed to carry out sophisticated, multiaxis operations. One particularly useful program is a serial combination of "load," "transport," an...

Enabling full-length evolutionary profiles based deep convolutional neural network for predicting DNA-binding proteins from sequence.

Sequence based DNA-binding protein (DBP) prediction is a widely studied biological problem. Sliding windows on position specific substitution matrices (PSSMs) rows predict DNA-binding residues well on known DBPs but the same models cannot be applied to unequally sized protein sequences. PSSM summaries representing column averages and their amino-acid wise versions have been effectively used for th...

Applying Deep Neural Network Analysis to High-Content Image-Based Assays.

The etiological underpinnings of many CNS disorders are not well understood. This is likely due to the fact that individual diseases aggregate numerou...

Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data.

BACKGROUND: Unsupervised machine learning methods (deep learning) have shown their usefulness with noisy single cell mRNA-sequencing data (scRNA-seq),...

A practical guide to intelligent image-activated cell sorting.

Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of singl...

BioGD: Bio-inspired robust gradient descent.

Recent research in machine learning pointed to the core problem of state-of-the-art models which impedes their widespread adoption in different domain...

Microbiome composition and implications for ballast water classification using machine learning.

Ballast water is a vector for global translocation of microorganisms, and should be monitored to protect human and environmental health. This study ut...

Deep learning-based selection of human sperm with high DNA integrity.

Despite the importance of sperm DNA to human reproduction, currently no method exists to assess individual sperm DNA quality prior to clinical selecti...

CT texture analysis for the prediction of KRAS mutation status in colorectal cancer via a machine learning approach.

PURPOSE: This study aimed to investigate whether a machine learning-based computed tomography (CT) texture analysis could predict the mutation status ...

Cancer classification and pathway discovery using non-negative matrix factorization.

OBJECTIVES: Extracting genetic information from a full range of sequencing data is important for understanding disease. We propose a novel method to e...

Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models.

BACKGROUND: In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are di...

Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition.

Microbial communities are ubiquitous and often influence macroscopic properties of the ecosystems they inhabit. However, deciphering the functional re...

C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods.

BACKGROUND AND OBJECTIVE: Over the last two decades, DNA microarray technology has emerged as a powerful tool for early cancer detection and preventio...

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most case...

A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS).

Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain...

Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a...

EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame.

Emerging RNA-based approaches to disease detection and gene therapy require RNA sequences that fold into specific base-pairing patterns, but computati...

Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a...

A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence.

We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural...

Computational and artificial neural network based study of functional SNPs of human LEPR protein associated with reproductive function.

Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the biological significance of functional single-nucleoti...