AIMC Journal:
IEEE transactions on computational biology and bioinformatics
Showing 41 to 50 of 56 articles
A Spectral Clustering-Based Approach for Balancing Data in TF-Target Gene Interaction Prediction Using Heterogeneous Network Embedding.
IEEE transactions on computational biology and bioinformatics
Feb 23, 2026
Identifying transcription factors (TFs) interacting with target genes plays a crucial role in regulating gene expression, providing deep insights into the molecular mechanisms involved in biological processes and diseases, while also opening new oppo...
A Novel Relative Distance Protein Fingerprint Algorithm for Searching DNA Mimic Proteins.
IEEE transactions on computational biology and bioinformatics
Feb 20, 2026
DNA mimic proteins are relatively obscure control factors that resemble DNA by mimicking its negatively charged distribution. They achieve this using negatively charged amino acids like aspartic acid (ASP/D) and glutamic acid (GLU/E). Known DNA mimic...
Deep-Q-Network in Multiview Ensemble Learning to Predict Anti-diabetic Peptide and Diabetic Types.
IEEE transactions on computational biology and bioinformatics
Feb 16, 2026
Diabetes mellitus disease has become a significant human health concern globally, causing cardiovascular complications, kidney disease, cerebrovascular accidents, etc. In humans, bioactive molecules, specifically Antidiabetic peptides (ADPs), target ...
SCImputation: Mitigating Feature Confounding From a Structural Causal Perspective for Data Imputation.
IEEE transactions on computational biology and bioinformatics
Feb 16, 2026
Missing data remain a critical challenge in data analysis, often leading to biased estimates and reduced reliability. Many imputation methods, operating under the assumption that similar instances share similar feature values, overlook the pivotal ro...
Deep Temporal Sequence Classification and Mathematical Modeling for Cell Tracking in Dense 3D Microscopy Videos of Bacterial Biofilms.
IEEE transactions on computational biology and bioinformatics
Feb 11, 2026
Automatic cell tracking in dense environments is plagued by inaccurate correspondences and misidentification of parent-offspring relationships. In this paper, we introduce a novel cell tracking algorithm named DenseTrack, which integrates deep learni...
AGEP_TWAS: A Deep Learning-based Framework for Predicting Gene Expression Levels in Tissues.
IEEE transactions on computational biology and bioinformatics
Feb 10, 2026
Accurate prediction of gene expression levels across different tissues is of great significance in understanding the functional roles of genes in various biological processes and assisting in transcriptome-wide association studies (TWAS). Traditional...
MMCL: A Multi-modal Contrastive Learning Framework for Molecular Property Prediction.
IEEE transactions on computational biology and bioinformatics
Feb 10, 2026
Accurately predicting molecular properties can identify more promising drug candidates and facilitate the process of drug discovery. There are advances in methods for molecular property prediction using self-supervised learning. However, most methods...
Rule-Based Protein Classification through Multi-Phase Feature Extraction Technique.
IEEE transactions on computational biology and bioinformatics
Feb 10, 2026
Protein sequence classification is a fundamental step toward functional annotation and biological analysis; however, most of the existing approaches rely on computationally expensive models or flat feature integration with limited interpretability. T...
Bayesian Hyperspherical Graph Mixture-of-Experts Deciphers Cell-Cell Interaction in Spatial Transcriptomics.
IEEE transactions on computational biology and bioinformatics
Feb 2, 2026
Spatial transcriptomics (ST) technologies have transformed our understanding of tissue biology by capturing gene expression with spatial context, enabling systematic analysis of cell-cell interactions (CCIs) and spatial domains in complex tissues. Ho...
Artificial Intelligence Driven Virtual Screening and Molecular Docking Approaches Identified LIFR, BTG2, EPHX2, and PAK3 as Targets and BI-2536, AP-24534, and AZ-628 as Repurposed Drugs for PDAC.
IEEE transactions on computational biology and bioinformatics
Jan 28, 2026
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal tumors worldwide, with limited effective treatments. Globally, the incidence of pancreatic cancer is expected to rise to 18.6 per 100,000 by 2050, with an average annual...
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