Genetics

Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation.

BACKGROUND: The introduction of next-generation sequencing (NGS) into molecular cancer diagnostics has led to an increase in the data available for the identification and evaluation of driver mutations and for defining personalized cancer treatment regimens. The meaningful combination of omics data, ie, pathogenic gene variants and alterations with other patient data, to understand the full pictur...

A deep learning approach to programmable RNA switches.

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch m...

Application of BERT to Enable Gene Classification Based on Clinical Evidence.

The identification of profiled cancer-related genes plays an essential role in cancer diagnosis and treatment. Based on literature research, the class...

lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.

Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease a...

Machine Learning to Improve the Sensing of Biomolecules by Conical Track-Etched Nanopore.

Single nanopore is a powerful platform to detect, discriminate and identify biomacromolecules. Among the different devices, the conical nanopores obta...

Deep neural network improves the estimation of polygenic risk scores for breast cancer.

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. I...

Recent advances on the machine learning methods in predicting ncRNA-protein interactions.

Recent transcriptomics and bioinformatics studies have shown that ncRNAs can affect chromosome structure and gene transcription, participate in the ep...

A Novel Strategy for the Development of Vaccines for SARS-CoV-2 (COVID-19) and Other Viruses Using AI and Viral Shell Disorder.

A model that predicts levels of coronavirus (CoV) respiratory and fecal-oral transmission potentials based on the shell disorder has been built using ...

Metabolic pathway inference using multi-label classification with rich pathway features.

Metabolic inference from genomic sequence information is a necessary step in determining the capacity of cells to make a living in the world at differ...

The application of deep learning for the classification of correct and incorrect SNP genotypes from whole-genome DNA sequencing pipelines.

A downside of next-generation sequencing technology is the high technical error rate. We built a tool, which uses array-based genotype information to ...

Characterizing CDK12-Mutated Prostate Cancers.

PURPOSE: Cyclin-dependent kinase 12 (CDK12) aberrations have been reported as a biomarker of response to immunotherapy for metastatic castration-resis...

Deep learning of immune cell differentiation.

Although we know many sequence-specific transcription factors (TFs), how the DNA sequence of cis-regulatory elements is decoded and orchestrated on th...

Genome-wide association study-based deep learning for survival prediction.

Informative and accurate survival prediction with individualized dynamic risk profiles over time is critical for personalized disease prevention and c...

LncMirNet: Predicting LncRNA-miRNA Interaction Based on Deep Learning of Ribonucleic Acid Sequences.

Long non-coding RNA (LncRNA) and microRNA (miRNA) are both non-coding RNAs that play significant regulatory roles in many life processes. There is cum...

Identification of risk features for complication in Gaucher's disease patients: a machine learning analysis of the Spanish registry of Gaucher disease.

BACKGROUND: Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the d...

A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity.

Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim w...

Keeping up with the genomes: efficient learning of our increasing knowledge of the tree of life.

BACKGROUND: It is a computational challenge for current metagenomic classifiers to keep up with the pace of training data generated from genome sequen...

Amplification Curve Analysis: Data-Driven Multiplexing Using Real-Time Digital PCR.

Information about the kinetics of PCR reactions is encoded in the amplification curve. However, in digital PCR (dPCR), this information is typically n...

Short k-mer abundance profiles yield robust machine learning features and accurate classifiers for RNA viruses.

High-throughput sequencing technologies have greatly enabled the study of genomics, transcriptomics and metagenomics. Automated annotation and classif...

Evaluating the informativeness of deep learning annotations for human complex diseases.

Deep learning models have shown great promise in predicting regulatory effects from DNA sequence, but their informativeness for human complex diseases...