AIMC Topic: Computational Biology
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HGLA: Biomolecular Interaction Prediction Based on Mixed High-Order Graph Convolution With Filter Network via LSTM and Channel Attention.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Predicting biomolecular interactions is significant for understanding biological systems. Most existing methods for link prediction are based on graph convolution. Although graph convolution methods are advantageous in extracting structure informatio...
Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules With Desirable Properties.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
In the past decade, Artificial Intelligence (AI) driven drug design and discovery has been a hot research topic in the AI area, where an important branch is molecule generation by generative models, from GAN-based models and VAE-based models to the l...
Machine Learning-Assisted High-Throughput Screening for Anti-MRSA Compounds.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
BACKGROUND: Antimicrobial resistance is a major public health threat, and new agents are needed. Computational approaches have been proposed to reduce the cost and time needed for compound screening.
Generative Adversarial Network-Based Augmentation With Noval 2-Step Authentication for Anti-Coronavirus Peptide Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
The virus poses a longstanding and enduring danger to various forms of life. Despite the ongoing endeavors to combat viral diseases, there exists a necessity to explore and develop novel therapeutic options. Antiviral peptides are bioactive molecules...
Enhancing Generalizability in Biomedical Entity Recognition: Self-Attention PCA-CLS Model.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
One of the primary tasks in the early stages of data mining involves the identification of entities from biomedical corpora. Traditional approaches relying on robust feature engineering face challenges when learning from available (un-)annotated data...
Employing Machine Learning Techniques to Detect Protein Function: A Survey, Experimental, and Empirical Evaluations.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
This review article delves deeply into the various machine learning (ML) methods and algorithms employed in discerning protein functions. Each method discussed is assessed for its efficacy, limitations, potential improvements, and future prospects. W...
Bi-SeqCNN: A Novel Light-Weight Bi-Directional CNN Architecture for Protein Function Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Deep learning approaches, such as convolution neural networks (CNNs) and deep recurrent neural networks (RNNs), have been the backbone for predicting protein function, with promising state-of-the-art (SOTA) results. RNNs with an in-built ability (i) ...
Improved Fuzzy Cognitive Maps for Gene Regulatory Networks Inference Based on Time Series Data.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Microarray data provide lots of information regarding gene expression levels. Due to the large amount of such data, their analysis requires sufficient computational methods for identifying and analyzing gene regulation networks; however, researchers ...
Graph Convolutional Network With Self-Supervised Learning for Brain Disease Classification.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Brain functional network (BFN) analysis has become a popular method for identifying neurological diseases at their early stages and revealing sensitive biomarkers related to these diseases. Due to the fact that BFN is a graph with complex structure, ...
Ense-i6mA: Identification of DNA N-Methyladenine Sites Using XGB-RFE Feature Selection and Ensemble Machine Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
DNA N-methyladenine (6mA) is an important epigenetic modification that plays a vital role in various cellular processes. Accurate identification of the 6mA sites is fundamental to elucidate the biological functions and mechanisms of modification. How...
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