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Computational Biology

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[PSI]-CIC: A Deep-Learning Pipeline for the Annotation of Sectored Saccharomyces cerevisiae Colonies.

Bulletin of mathematical biology
The prion phenotype in yeast manifests as a white, pink, or red color pigment. Experimental manipulations destabilize prion phenotypes, and allow colonies to exhibit (red) sectored phenotypes within otherwise completely white colonies. Further inve...

Representing DNA for machine learning algorithms: A primer on one-hot, binary, and integer encodings.

Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology
This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning interven...

AEmiGAP: AutoEncoder-Based miRNA-Gene Association Prediction Using Deep Learning Method.

International journal of molecular sciences
MicroRNAs (miRNAs) play a crucial role in gene regulation and are strongly linked to various diseases, including cancer. This study presents AEmiGAP, an advanced deep learning model that integrates autoencoders with long short-term memory (LSTM) netw...

AlzGenPred - CatBoost-based gene classifier for predicting Alzheimer's disease using high-throughput sequencing data.

Scientific reports
AD is a progressive neurodegenerative disorder characterized by memory loss. Due to the advancement in next-generation sequencing, an enormous amount of AD-associated genomics data is available. However, the information about the involvement of these...

Geometric Molecular Graph Representation Learning Model for Drug-Drug Interactions Prediction.

IEEE journal of biomedical and health informatics
Drug-drug interaction (DDI) can trigger many adverse effects in patients and has emerged as a threat to medicine and public health. Therefore, it is important to predict potential drug interactions since it can provide combination strategies of drugs...

Multi-View Multiattention Graph Learning With Stack Deep Matrix Factorization for circRNA-Drug Sensitivity Association Identification.

IEEE journal of biomedical and health informatics
Identifying circular RNA (circRNA)-drug sensitivity association (CDsA) is crucial for advancing drug development. As conducting traditional wet experiments for determining CDsA is costly and inefficient, calculation methods have already proven to be ...

Predicting miRNA-Disease Associations Based on Spectral Graph Transformer With Dynamic Attention and Regularization.

IEEE journal of biomedical and health informatics
Extensive research indicates that microRNAs (miRNAs) play a crucial role in the analysis of complex human diseases. Recently, numerous methods utilizing graph neural networks have been developed to investigate the complex relationships between miRNAs...

Identifying Associations Between Small Nucleolar RNAs and Diseases via Graph Convolutional Network and Attention Mechanism.

IEEE journal of biomedical and health informatics
Research has shown that small nucleolar RNAs (snoRNAs) play crucial roles in various biological processes, and understanding disease pathogenesis by studying their relationship with diseases is beneficial. Currently, known associations are insufficie...

Self-Supervised Pre-Training via Multi-View Graph Information Bottleneck for Molecular Property Prediction.

IEEE journal of biomedical and health informatics
Molecular representation learning has remarkably accelerated the development of drug analysis and discovery. It implements machine learning methods to encode molecule embeddings for diverse downstream drug-related tasks. Due to the scarcity of labele...

Machine learning-based analysis of programmed cell death types and key genes in intervertebral disc degeneration.

Apoptosis : an international journal on programmed cell death
Intervertebral disc degeneration (IVDD) is intricately associated with various forms of programmed cell death (PCD). Identifying key PCD types and associated genes is essential for understanding the molecular mechanisms underlying IVDD and discoverin...