IEEE/ACM Transactions on Computational Biology and Bioinformatics

Aims & Scope

IEEE/ACM Transactions on Computational Biology and Bioinformatics emphasizes the algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development of biological databases; and important biological results that are obtained from the use of these methods, programs and databases; the emerging field of Systems Biology, where many forms of data are used to create a computer-based model of a complex biological system.

The publication represents a mixture of three research modalities: a) fundamental methodological, algorithmic, mathematical and statistical research directly motivated by biological issues; b) papers focusing on experimental and implementation issues; and c) papers on serious application of methods and programs that lead to discoveries of biological significance.

Increasingly, papers contain elements of all three modalities.

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; functional genomics; molecular docking and drug design; computational problems in genetics such as linkage and QTL analysis, linkage disequilibrium analysis in populations, and haplotype determination; systems biology.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3.4
2024	3.60

Journal Rank

Year	Value
2024	6820

Journal Citation Indicator

Year	Value
2024	4060

SJR (SCImago Journal Rank)

Year	Value
2024	0.797

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	96

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Biochemistry, Genetics and Molecular Biology and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Biclustering algorithms for biological data analysis: a survey

  Citation: 1433

  Authors: S.C., A.L.

• XGBoost Model for Chronic Kidney Disease Diagnosis

  Citation: 589

  Authors: Adeola, Qing-Guo

• Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images

  Citation: 536

  Authors: Ying, Shuangjia, Liang, Xiang, Xiaodong, Ziwang, Jianwen, Ruixuan, Huiying, Yutian, Jun, Yunfei, Yuedong

• A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis

  Citation: 505

  Authors: C., J., S., D., A., C., V., R., H., A.

• Supervised, Unsupervised, and Semi-Supervised Feature Selection: A Review on Gene Selection

  Citation: 502

  Authors: Jun Chin, Andri, Habibollah, Haza Nuzly Abdull

• GenomeTools: A Comprehensive Software Library for Efficient Processing of Structured Genome Annotations

  Citation: 422

  Authors: Gordon, Sascha, Stefan

• CNN-RNN Based Intelligent Recommendation for Online Medical Pre-Diagnosis Support

  Citation: 355

  Authors: Xiaokang, Yue, Wei

• Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification

  Citation: 329

  Authors: Yong, Dun-wei, Jian

• Efficient Detection of Network Motifs

  Citation: 320

  Authors: Sebastian

• EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications

  Citation: 283

  Authors: Xiaotong, Zehong, Alireza, Peng, Dongrui, Tzyy-Ping, Chin-Teng

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