Genetics

Biomarker identification by reversing the learning mechanism of an autoencoder and recursive feature elimination.

RNA-Seq has made significant contributions to various fields, particularly in cancer research. Recent studies on differential gene expression analysis and the discovery of novel cancer biomarkers have extensively used RNA-Seq data. New biomarker identification is essential for moving cancer research forward, and early cancer diagnosis improves patients' chances of recovery and increases life expec...

iDRBP-ECHF: Identifying DNA- and RNA-binding proteins based on extensible cubic hybrid framework.

Proteins interact with nucleic acids to regulate the life activities of organisms. Therefore, how to accurately and efficiently identify nucleic acid-binding proteins (NABPs) is particularly significant. Some sequence-based computational methods have been proposed to identify DNA- and RNA-binding proteins in previous studies. However, the benchmark datasets used by these methods ignore the proport...

Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods.

The cell cycle is composed of a series of ordered, highly regulated processes through which a cell grows and duplicates its genome and eventually divi...

De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks.

With the emergence of high throughput single cell techniques, the understanding of the molecular and cellular diversity of mammalian organs have rapid...

Nested epistasis enhancer networks for robust genome regulation.

Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhance...

Multiclass Classification for Detection of COVID-19 Infection in Chest X-Rays Using CNN.

Coronavirus took the world by surprise and caused a lot of trouble in all the important fields in life. The complexity of dealing with coronavirus lie...

Identifying the tumor location-associated candidate genes in development of new drugs for colorectal cancer using machine-learning-based approach.

Numerous studies have been conducted to elucidate the relation of tumor proximity to cancer prognosis and treatment efficacy in colorectal cancer. How...

Measuring internal inequality in capsule networks for supervised anomaly detection.

In this paper we explore the use of income inequality metrics such as Gini or Palma coefficients as a tool to identify anomalies via capsule networks....

DeepIDA: Predicting Isoform-Disease Associations by Data Fusion and Deep Neural Networks.

Alternative splicing produces different isoforms from the same gene locus, it is an important mechanism for regulating gene expression and proteome di...

DeepBarcoding: Deep Learning for Species Classification Using DNA Barcoding.

DNA barcodes with short sequence fragments are used for species identification. Because of advances in sequencing technologies, DNA barcodes have grad...

DeepIII: Predicting Isoform-Isoform Interactions by Deep Neural Networks and Data Fusion.

Alternative splicing enables a gene translating into different isoforms and into the corresponding proteoforms, which actually accomplish various biol...

IDRBP-PPCT: Identifying Nucleic Acid-Binding Proteins Based on Position-Specific Score Matrix and Position-Specific Frequency Matrix Cross Transformation.

DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) are two important nucleic acid-binding proteins (NABPs), which play important roles in bio...

ZayyuNet - A Unified Deep Learning Model for the Identification of Epigenetic Modifications Using Raw Genomic Sequences.

Epigenetic modifications have a vital role in gene expression and are linked to cellular processes such as differentiation, development, and tumorigen...

Predicting RBP Binding Sites of RNA With High-Order Encoding Features and CNN-BLSTM Hybrid Model.

RNA binding protein (RBP) is extensively involved in various cellular regulatory processes through the interaction with RNAs. Capturing the RBP bindin...

Latent Representation of the Human Pan-Celltype Epigenome Through a Deep Recurrent Neural Network.

The availability of thousands of assays of epigenetic activity necessitates compressed representations of these data sets that summarize the epigeneti...

Deep Learning-Aided Automated Pneumonia Detection and Classification Using CXR Scans.

The COVID-19 pandemic has caused a worldwide catastrophe and widespread devastation that reeled almost all countries. The pandemic has mounted pressur...

iRNA5hmC-HOC: High-order correlation information for identifying RNA 5-hydroxymethylcytosine modification.

RNA 5-hydroxymethylcytosine (5 hmC) is an important RNA modification, which plays vital role in several biological processes. Currently, it is a hot t...

Protocol to estimate cell type proportions from bulk RNA-seq using DAISM-DNN.

Computational protocols for cell type deconvolution from bulk RNA-seq data have been used to understand cellular heterogeneity in disease-related samp...

Automatic scoring of COVID-19 severity in X-ray imaging based on a novel deep learning workflow.

In this study, we propose a two-stage workflow used for the segmentation and scoring of lung diseases. The workflow inherits quantification, qualifica...

Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study.

Neurotransmitters, such as dopamine and serotonin, are responsible for mediating a wide array of neurologic functions, from memory to motivation. From...