International Journal of Bioinformatics and Computational Biology
Bio Technology ISSN 2583-9977 2 issues a year Hybrid open accessWhat does hybrid open access mean? This journal has two kinds of articles. Open access articles are free for anyone to read; the author pays an article processing charge for that. All other articles are for subscribers. Authors can also publish at no cost under the subscription-based option.
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About the journal
International Journal of Bioinformatics and Computational Biology is a peer-reviewed hybrid open-access journal launched in 2023 concerning recent advancements and emerging technology in computational biology and bioinformatics. Journal also covers a wide range of topics including synthetic biology and structural genomics. Journal publishes both experimental and theoretical papers.
Journal metrics
Counted from this archive, not supplied by anyone.
- 46Articles published
- 14Published in 2026
- 104Authors
- 1Open access
Journal information
- Title
- International Journal of Bioinformatics and Computational Biology
- Issues per year
- 2 issues
- ISSN
- 2583-9977
- Publisher
- STM Journals
- DOI
- 10.37628/IJBCB
- Starting year
- 2023
- Subject
- Bio Technology
- Publication format
- Hybrid open access
- Language
- English
- Copyright policy
- CC BY-NC-ND 4.0
- Type
- Peer-reviewed journal (refereed)
- Article processing charge
- ₹10,000 in India · $400 outside India
- Subscription-based publication
- No cost. Author copy, DOI and certificate are chargeable.
Indexed in
Editorial board
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Editor-in-Chief
Biostatistics and Bioinformatics, Georgetown University, USA
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Associate Editor-in-Chief
Physical and Life Sciences, Guru Nanak Institutions, India.
Latest articles
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Predicting Cardiovascular Disease Risk Using Machine Learning: A Comprehensive Review
Abstract: Cardiovascular diseases (CVDs) are the prevalent morbid and fatal conditions worldwide. Repetition is key to stopping these diseases before they start and before they appear. With the advancement of data analytics and AI, machine learning (ML) has emerged as a powerful tool for predicting CVD risk and delivering personalized healthcare solutions. This review comprehensively summarizes the latest trends in the use of machine learning techniques to predict cardiovascular disease risk. …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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A Novel WPFM-Transformer Framework for DNA Sequence Classification using FASTA Data
Abstract: The identification of genetic variants, tracing of disease-associated mutations, and the reconstruction of evolutionary relationships from raw sequence data are all achieved by the analysis of DNA sequence. The FASTA format is plain text and is an easy-to-read format, which is why it has endured four decades of the field's growth into bioinformatics. Classical alignment programs like BLAST and Smith-Waterman work well with small data sets, but are limited by …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Improving Reliability of Deep Learning System Under Distribution Shift Via Feature-Space Out-of-Distribution Detection
Abstract: Deep learning systems achieve strong predictive performance under independently and identically distributed conditions; however, their reliability can decline significantly when exposed to distribution shifts during deployment. This decline is often accompanied by overconfident predictions, which can introduce serious risks in safety-critical applications. In this work, we explore whether explicitly modeling the structure of the latent feature space can improve reliability through more effective out-ofdistribution detection. A statistically grounded framework based …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 66–76 Read article
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Privacy-by-Design in Modern Data Science: A Systematic Review of Differential Privacy and Federated Analytics
Abstract: Okay so here is a problem that has been bothering us for a while. Everyone talks about how data is the new oil, how data-driven decisions are transforming healthcare, finance, governance, all of it. And that is true. But there is this massive elephant in the room that a lot of people in the data science community sort of wave away: privacy. The more useful the data, the more personal …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Bioinformatics and Medicine: Bringing Data to the Bedside
Abstract: From being an empirical and experience-based practice, modern medicine has transformed into a codified and research-based discipline, known as Evidence-Based Medicine (EBM). Though EBM has greatly enhanced the quality of medical practice through population-scale clinical trials, it still has limitations in managing biologically diverse patient populations, especially when dealing with clinical outliers who respond in an unusual way to standard treatments. With the rapid progress in genomics, proteomics, and high-throughput …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 41–46 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 26–40 Read article
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Differential Gene Expression Analysis of Human Atrial Fibroblasts Reveals Dysregulation of RNA Metabolism and Translational Machinery in Atrial Fibrillation
Abstract: Atrial fibrillation (AF) is a complex cardiac arrhythmia characterized by extensive structural remodeling and the activation of atrial fibroblasts, which drive the progression of fibrosis. To identify the underlying transcriptomic alterations, we analyzed six human atrial fibroblast RNA-Seq datasets (three control and three AF) retrieved from the Sequence Read Archive. After performing rigorous quality control and adapter trimming, we aligned the reads to the GRCh38 human reference genome using a …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 15–25 Read article