AIMC Topic: Models, Genetic

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A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BMC genomics
BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the induction of cancer through epigenetic regulation, transcriptional regulation, post-transcriptional regulation and other aspects, thus participating ...

Prediction of microbial communities for urban metagenomics using neural network approach.

Human genomics
BACKGROUND: Microbes are greatly associated with human health and disease, especially in densely populated cities. It is essential to understand the microbial ecosystem in an urban environment for cities to monitor the transmission of infectious dise...

Human mitochondrial genome compression using machine learning techniques.

Human genomics
BACKGROUND: In recent years, with the development of high-throughput genome sequencing technologies, a large amount of genome data has been generated, which has caused widespread concern about data storage and transmission costs. However, how to effe...

Predicting CRISPR/Cas9-Induced Mutations for Precise Genome Editing.

Trends in biotechnology
SpCas9 creates blunt end cuts in the genome and generates random and unpredictable mutations through error-prone repair systems. However, a growing body of recent evidence points instead to Cas9-induced staggered end generation, nonrandomness of muta...

Designing Eukaryotic Gene Expression Regulation Using Machine Learning.

Trends in biotechnology
Controlling the expression of genes is one of the key challenges of synthetic biology. Until recently fine-tuned control has been out of reach, particularly in eukaryotes owing to their complexity of gene regulation. With advances in machine learning...

Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response.

BMC biology
BACKGROUND: Identification of functional non-coding variants and their mechanistic interpretation is a major challenge of modern genomics, especially for precision medicine. Transcription factor (TF) binding profiles and epigenomic landscapes in refe...

A Guide for Using Deep Learning for Complex Trait Genomic Prediction.

Genes
Deep learning (DL) has emerged as a powerful tool to make accurate predictions from complex data such as image, text, or video. However, its ability to predict phenotypic values from molecular data is less well studied. Here, we describe the theoreti...

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data.

Scientific reports
Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machin...

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

Genome research
A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a unified population-genetic and machine-learning model, called inear llele-pecific election nferenc ...