Genetics

DIRECTION: a machine learning framework for predicting and characterizing DNA methylation and hydroxymethylation in mammalian genomes.

MOTIVATION: 5-Methylcytosine and 5-Hydroxymethylcytosine in DNA are major epigenetic modifications known to significantly alter mammalian gene expression. High-throughput assays to detect these modifications are expensive, labor-intensive, unfeasible in some contexts and leave a portion of the genome unqueried. Hence, we devised a novel, supervised, integrative learning framework to perform whole-...

DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

MOTIVATION: Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of adjacent base pairs, etc. Several methods have been developed to jointly account for DNA sequence and shape properties in predicting TF binding affini...

Impact of Clinical Parameters in the Intrahost Evolution of HIV-1 Subtype B in Pediatric Patients: A Machine Learning Approach.

Determining the factors modulating the genetic diversity of HIV-1 populations is essential to understand viral evolution. This study analyzes the rela...

Successful treatment with afatinib for pancreatic metastasis of lung adenocarcinoma: a case report.

Metastatic lung cancer of the pancreas is rare and optimal treatment protocols have not been determined. An asymptomatic 53-year-old man with primary ...

Using neural networks for reducing the dimensions of single-cell RNA-Seq data.

While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and fin...

A cargo-sorting DNA robot.

Two critical challenges in the design and synthesis of molecular robots are modularity and algorithm simplicity. We demonstrate three modular building...

An efficient graph kernel method for non-coding RNA functional prediction.

MOTIVATION: The importance of RNA protein-coding gene regulation is by now well appreciated. Non-coding RNAs (ncRNAs) are known to regulate gene expre...

A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data.

Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulatio...

Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets.

Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection o...

CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.

MOTIVATION: Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucle...

Identification of human flap endonuclease 1 (FEN1) inhibitors using a machine learning based consensus virtual screening.

Human Flap endonuclease1 (FEN1) is an enzyme that is indispensable for DNA replication and repair processes and inhibition of its Flap cleavage activi...

Identification of microRNA precursors using reduced and hybrid features.

MicroRNAs (also called miRNAs) are a group of short non-coding RNA molecules. They play a vital role in the gene expression of transcriptional and pos...

Denoising genome-wide histone ChIP-seq with convolutional neural networks.

MOTIVATION: Chromatin immune-precipitation sequencing (ChIP-seq) experiments are commonly used to obtain genome-wide profiles of histone modifications...

When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants.

MOTIVATION: Loss-of-function genetic variants are frequently associated with severe clinical phenotypes, yet many are present in the genomes of health...

Image-based surrogate biomarkers for molecular subtypes of colorectal cancer.

MOTIVATION: Whole genome expression profiling of large cohorts of different types of cancer led to the identification of distinct molecular subcategor...

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator fo...

HIPred: an integrative approach to predicting haploinsufficient genes.

MOTIVATION: A major cause of autosomal dominant disease is haploinsufficiency, whereby a single copy of a gene is not sufficient to maintain the norma...

nala: text mining natural language mutation mentions.

MOTIVATION: The extraction of sequence variants from the literature remains an important task. Existing methods primarily target standard (ST) mutatio...

The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations.

OBJECTIVE: This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu ), an interactive online application for c...

RED-ML: a novel, effective RNA editing detection method based on machine learning.

With the advancement of second generation sequencing techniques, our ability to detect and quantify RNA editing on a global scale has been vastly impr...