AIMC Topic: Databases, Genetic

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Data integration by fuzzy similarity-based hierarchical clustering.

BMC bioinformatics
BACKGROUND: High throughput methods, in biological and biomedical fields, acquire a large number of molecular parameters or omics data by a single experiment. Combining these omics data can significantly increase the capability for recovering fine-tu...

Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.

Biomolecules
An effective feature extraction method is key to improving the accuracy of a prediction model. From the Gene Expression Omnibus (GEO) database, which includes 13,487 genes, we obtained microarray gene expression data for 238 samples from colorectal c...

A system for automatically extracting clinical events with temporal information.

BMC medical informatics and decision making
BACKGROUND: The popularization of health and medical informatics yields huge amounts of data. Extracting clinical events on a temporal course is the foundation of enabling advanced applications and research. It is a structure of presenting informatio...

Predicting essential genes of 41 prokaryotes by a semi-supervised method.

Analytical biochemistry
Essential genes are vitally important to the survival and reproduction of organisms. Many machine learning methods have been widely employed to predict essential genes and have obtained satisfactory results. However, most of these methods are supervi...

m7GPredictor: An improved machine learning-based model for predicting internal m7G modifications using sequence properties.

Analytical biochemistry
As one of the most important post-transcriptional modifications, the N7-methylguanosine (m7G) plays a key role in many RNA processing events. The accurate identification of m7G is crucial for elucidating its biological significance and future applica...

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

Genes
DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods use either differentially methylated CpG sites or combined CpG sites, namely differentially methylate...

Machine learning-based classification and diagnosis of clinical cardiomyopathies.

Physiological genomics
Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common types of cardiomyopathies leading to heart failure. Accurate diagnostic classification of different types of cardiomyopathies is critical for precision medicine in clinical...

MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature.

Scientific reports
In spite of the efforts in developing and maintaining accurate variant databases, a large number of disease-associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an effort to extract this informat...

EDeepSSP: Explainable deep neural networks for exact splice sites prediction.

Journal of bioinformatics and computational biology
Splice site prediction is crucial for understanding underlying gene regulation, gene function for better genome annotation. Many computational methods exist for recognizing the splice sites. Although most of the methods achieve a competent performanc...