IEEE-ACM Transactions on Computational Biology and Bioinformatics

Scope & Guideline

Exploring the Intersection of Data and Life Sciences

Introduction

Explore the comprehensive scope of IEEE-ACM Transactions on Computational Biology and Bioinformatics through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore IEEE-ACM Transactions on Computational Biology and Bioinformatics in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN1545-5963
PublisherIEEE COMPUTER SOC
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2004 to 2024
AbbreviationIEEE ACM T COMPUT BI / IEEE-ACM Trans. Comput. Biol. Bioinform.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314

Aims and Scopes

The IEEE-ACM Transactions on Computational Biology and Bioinformatics focuses on the intersection of computational methods and biological data. It aims to advance the field by publishing high-quality research that utilizes innovative computational techniques to solve biological problems. The journal encompasses a wide array of topics, methodologies, and applications in computational biology and bioinformatics, emphasizing the integration of data analysis, modeling, and computational tools.
  1. Computational Biology:
    The journal publishes research that applies computational methods to understand biological systems, focusing on the development of algorithms and software tools for analyzing biological data.
  2. Bioinformatics Applications:
    It emphasizes practical applications of computational techniques in bioinformatics, including genomic, transcriptomic, and proteomic data analysis, as well as systems biology.
  3. Machine Learning and AI Techniques:
    A significant portion of the research involves the application of machine learning and artificial intelligence to predict biological outcomes, classify biological samples, and improve diagnostic processes.
  4. Data Integration and Analysis:
    The journal explores methodologies for integrating diverse biological data sources, including multi-omics data, to provide comprehensive insights into biological questions.
  5. Novel Algorithm Development:
    Research focuses on the creation of new algorithms and computational models that enhance the analysis and interpretation of complex biological data.
  6. Interdisciplinary Approaches:
    The journal encourages interdisciplinary research, combining insights from biology, computer science, and statistics to address complex biological challenges.
Recent publications highlight several emerging themes and trends that indicate a shift in research focus within the journal. These trends reflect the evolving landscape of computational biology and bioinformatics, driven by technological advancements and the increasing complexity of biological data.
  1. Deep Learning Applications:
    There is a marked increase in the application of deep learning techniques across various domains of computational biology, including genomics, proteomics, and imaging, showcasing their effectiveness in predictive modeling and classification tasks.
  2. Federated Learning and Privacy-Preserving Methods:
    Emerging themes around federated learning and privacy-preserving methods are gaining traction, particularly in medical applications, reflecting a growing concern for data privacy in health-related research.
  3. Integration of Multi-Omics Data:
    Research focusing on the integration of multi-omics data is becoming more prevalent, as it allows for a more comprehensive understanding of biological systems and disease mechanisms.
  4. Blockchain for Data Security:
    The application of blockchain technology for securing biological data and ensuring data integrity is an emerging area of interest, especially in the context of personalized medicine and health informatics.
  5. Explainable AI (XAI):
    There is a growing emphasis on explainable AI methods, aiming to enhance the interpretability of complex models and ensure that predictions are understandable to biologists and clinicians.
  6. Smart Healthcare Systems:
    Research is increasingly focused on developing smart healthcare systems that leverage AI and big data analytics for real-time monitoring, diagnosis, and treatment recommendations.

Declining or Waning

While the journal continues to thrive in many areas, certain themes have shown signs of waning interest or frequency in recent publications. This may reflect shifts in research focus, funding, or the emergence of new methodologies.
  1. Traditional Statistical Methods:
    There has been a noticeable decline in the use of traditional statistical methods for biological data analysis, as more researchers opt for advanced machine learning techniques that offer better predictive performance.
  2. Basic Sequence Alignment Techniques:
    The frequency of publications focusing solely on basic sequence alignment methods has decreased, likely due to the advent of more complex and efficient algorithms that integrate multiple biological data types.
  3. Single-Omics Analysis:
    Research dedicated to single-omics approaches is less prevalent as the field moves towards multi-omics integration, which provides a more holistic view of biological systems.
  4. Laboratory-Based Experimental Techniques:
    With the rise of computational methods, there is a decline in research that primarily focuses on laboratory-based experimental techniques without a significant computational component.
  5. Basic Visualization Techniques:
    The use of basic data visualization techniques has decreased as more sophisticated and interactive visualization tools become available, allowing for enhanced data interpretation.

Similar Journals

Computation

Exploring the frontiers of computational methodologies.
Publisher: MDPIISSN: Frequency: 12 issues/year

Computation, published by MDPI, is an esteemed open-access journal that has been contributing to the fields of applied mathematics and computer science since its inception in 2013. With an E-ISSN of 2079-3197, this Swiss-based journal operates under a philosophy of free knowledge dissemination, allowing researchers, professionals, and students globally to access high-quality content without financial barriers. Recognized for its rigorous peer-review process, Computation is currently categorized in the Q2 and Q3 quartiles across significant domains, including Applied Mathematics (#181/635), Theoretical Computer Science (#52/130), and Modeling and Simulation (#138/324). As it converges towards 2024, the journal continues to attract innovative and impactful research aimed at advancing theoretical frameworks and practical applications within these disciplines. Joining the Computation community not only enriches individual research portfolios but also contributes to the broader conversation on computational methodologies and their applications in solving real-world problems.

Bioinformatics and Biology Insights

Bridging computational methods with biological breakthroughs.
Publisher: SAGE PUBLICATIONS LTDISSN: 1177-9322Frequency: 1 issue/year

Bioinformatics and Biology Insights is a premier open-access journal dedicated to advancing the frontiers of bioinformatics and biology. Published by SAGE Publications Ltd, this journal is a leading platform for disseminating high-quality research that integrates computational methods with biological insights. Since its inception in 2007, the journal has garnered significant recognition, reflecting its commitment to excellence, as evidenced by its impressive impact factor and a strong presence across multiple quartiles in applied mathematics, biochemistry, and computational sciences. With a rank of Q1 in both Applied Mathematics and Computational Mathematics and various other notable rankings in related fields, it serves as an essential resource for researchers, professionals, and students seeking cutting-edge knowledge and innovations. The journal's open-access model ensures that findings are readily available, fostering collaboration and advancement in this dynamic field. Through its comprehensive scope and rigorous peer-review process, Bioinformatics and Biology Insights continues to play a pivotal role in shaping the future of biological research and computational methodologies.

Statistical Applications in Genetics and Molecular Biology

Unlocking Genetic Insights Through Statistical Expertise
Publisher: WALTER DE GRUYTER GMBHISSN: 2194-6302Frequency:

Statistical Applications in Genetics and Molecular Biology, published by WALTER DE GRUYTER GMBH, serves as a vital academic platform for researchers and professionals dedicated to the integration of statistical methodologies within the fields of genetics and molecular biology. Established in Germany, this interdisciplinary journal, with an ISSN of 2194-6302 and E-ISSN 1544-6115, seeks to bridge the gap between statistical theory and biological applications, making it an essential reading for those engaged in data analysis, biological research, and computational methods. Despite its current Q4 ranking in key categories such as Computational Mathematics and Genetics, the journal continues to strive for academic rigor and relevance, addressing contemporary challenges and advancements in the field. The journal encourages the submission of high-quality, peer-reviewed research that showcases innovative statistical approaches to genetic and molecular data, providing valuable insights and fostering collaboration among scientists. Exploratory or applied studies that demonstrate effective statistical applications are particularly welcomed, ensuring that both novel and established methodologies are discussed, alongside practical case studies that advance the understanding of biological phenomena. As an open-access journal, it aims to widen the accessibility of cutting-edge research, emphasizing the importance of transparency and sharing knowledge among the scientific community.

BMC BIOINFORMATICS

Transforming Biological Research with Cutting-Edge Computational Tools.
Publisher: BMCISSN: 1471-2105Frequency: 1 issue/year

BMC Bioinformatics is a leading open-access journal published by BMC, dedicated to the rapidly evolving field of bioinformatics. With its inception in 2000, the journal has established itself as an essential resource for researchers, professionals, and students alike, disseminating high-quality research that bridges the gap between biology and computational science. BMC Bioinformatics holds a reputable Q1 ranking in Applied Mathematics and Computer Science Applications, and a Q2 ranking in both Biochemistry and Structural Biology, reflecting its significant impact in these interdisciplinary fields. The journal's broad scope encompasses innovative methodologies, tools, and applications that drive progress in biological research through computational approaches. With open access since its inception, the journal ensures unrestricted availability of cutting-edge research findings, promoting knowledge sharing and collaboration in the global scientific community. As it continues to publish advancements up to 2024, BMC Bioinformatics remains a cornerstone for those seeking to enhance their understanding of bioinformatics and its vital role in modern science.

JOURNAL OF COMPUTATIONAL BIOLOGY

Empowering Researchers with Cutting-edge Computational Biology Insights
Publisher: MARY ANN LIEBERT, INCISSN: 1066-5277Frequency: 12 issues/year

JOURNAL OF COMPUTATIONAL BIOLOGY, published by Mary Ann Liebert, Inc., serves as a premier platform for the dissemination of groundbreaking research at the intersection of biological sciences and computational methods. Established in 1994, this journal provides a valuable resource for researchers, professionals, and students interested in the evolving fields of computational mathematics and biology. With a commendable Q2 ranking in several pertinent categories such as Computational Mathematics and Modeling and Simulation, it emphasizes high-quality studies that propel understanding and innovation in these areas. Although the journal currently operates under traditional access options, it plays a crucial role in fostering scholarly communication and collaboration among a diverse audience, advancing knowledge in genetics, molecular biology, and beyond. The journal's continual evolution, with a commitment to publish until at least 2024, positions it as a critical resource in the fast-paced world of computational biology.

International Journal of Data Mining and Bioinformatics

Advancing Knowledge in Data Mining and Bioinformatics.
Publisher: INDERSCIENCE ENTERPRISES LTDISSN: 1748-5673Frequency: 4 issues/year

The International Journal of Data Mining and Bioinformatics, published by InderScience Enterprises Ltd, stands as a crucial platform for researchers and professionals dedicated to the intersection of data science and biological informatics. With its ISSN 1748-5673 and E-ISSN 1748-5681, this journal captures the essence of innovative research from 2006 to 2024. Though indexed in the Q4 category for Biochemistry, Genetics and Molecular Biology and Information Systems, it maintains a respectable Q3 status in Library and Information Sciences, reflecting its growing influence within the academic community. The journal also provides insightful contributions to the fields of big data analytics, machine learning, and computational biology. Although it is not currently an open-access journal, its relevance is underscored by its Scopus rankings, indicating a solid standing in the disciplines it encompasses. Researchers, students, and practitioners in data mining and bioinformatics are encouraged to explore the findings and methodologies presented, paving the way for future innovations in this dynamic field.

GigaScience

Pioneering Open Access Research in Medicine and Technology
Publisher: OXFORD UNIV PRESSISSN: 2047-217XFrequency: 1 issue/year

GigaScience, published by Oxford University Press, is a pioneering open-access journal that has made significant strides in the fields of Medicine, Health Informatics, and Computer Science Applications since its inception in 2012. With an impressive impact factor and a consistent ranking in the Q1 category across multiple disciplines, GigaScience is recognized as an essential resource for researchers dedicated to advancing data-driven science. The journal's commitment to high-quality research is reflected in its Scopus rankings, placing it in the top 5% and 4% of its categories. As an open-access journal, GigaScience ensures that vital research is accessible to a global audience, fostering collaboration and innovation in an increasingly interconnected research landscape. Researchers, professionals, and students alike will find GigaScience instrumental in exploring the intersection of computational technology and life sciences, as it frequently publishes groundbreaking studies that shape future inquiries in these dynamic fields.

Journal of Bioinformatics and Computational Biology

Catalyzing Interdisciplinary Collaboration in Computational Biology
Publisher: WORLD SCIENTIFIC PUBL CO PTE LTDISSN: 0219-7200Frequency: 6 issues/year

The Journal of Bioinformatics and Computational Biology, published by WORLD SCIENTIFIC PUBL CO PTE LTD, serves as a significant platform for disseminating innovative research in the dynamic fields of bioinformatics and computational biology. With an ISSN of 0219-7200 and an E-ISSN of 1757-6334, this journal facilitates the exchange of ideas and advancements from its inception in 2003 and continues to be pivotal through 2024. Despite its classification in the lower quartiles—Q4 in Biochemistry and Q4 in Molecular Biology, along with Q3 in Computer Science Applications—the journal remains a valuable resource for researchers and students alike, as it emphasizes interdisciplinary approaches essential for tackling complex biological problems through computational methods. Located in Singapore, the journal encourages submissions of high-quality, peer-reviewed articles that offer insights into computational techniques that empower biological research. Although this journal does not offer open access options, its contributions to research are increasingly recognized across various academic platforms. As the field evolves rapidly, this journal continues to attract a growing readership, making it an essential reference point for anyone interested in the intersection of biology and computer science.

BioData Mining

Pioneering New Paths in Computational Biology
Publisher: BMCISSN: 1756-0381Frequency: 1 issue/year

BioData Mining is a distinguished open access journal published by BMC, focusing on the dynamic intersection of bioinformatics, computational mathematics, and molecular biology. Since its inception in 2008, this journal has provided a critical platform for researchers and professionals to publish their findings, contributing significantly to the collective knowledge in fields such as biochemistry, computational theory, and genetics. With a robust impact factor and a commendable h-index, BioData Mining continues to be a vital resource for academic and industrial advancements, ranked in the top quartiles in various categories according to the 2023 metrics. The journal's commitment to open access ensures that cutting-edge research is readily available to the global scientific community, thereby enhancing visibility and fostering collaboration among scholars. Whether you are a researcher, student, or practitioner, engaging with BioData Mining will equip you with relevant insights and developments in the fast-evolving realm of bioinformatics.

BRIEFINGS IN BIOINFORMATICS

Advancing Knowledge at the Intersection of Biology and Technology
Publisher: OXFORD UNIV PRESSISSN: 1467-5463Frequency: 6 issues/year

BRIEFINGS IN BIOINFORMATICS is a premier academic journal dedicated to the dynamic field of bioinformatics, published by Oxford University Press. With a prestigious standing reflected in its Q1 quartile rankings in both Information Systems and Molecular Biology, this journal serves as an essential resource for researchers, professionals, and students eager to explore the intersection of biology and computational sciences. The journal not only publishes high-impact research articles but also reviews and critical commentaries that push the boundaries of understanding in bioinformatics. As it converges its objectives towards fostering innovation and knowledge dissemination from 2000 to 2024, BRIEFINGS IN BIOINFORMATICS offers rich insights that remain pivotal to advancements in genomic studies, data integration, and computational tools. Its ranking in the top percentiles of Scopus—30th among 394 in Computer Science and 44th among 410 in Molecular Biology—underscores the journal's influential presence in the academic community. Engaging with the latest research and trends, this journal is integral for anyone invested in the future of life sciences and data analytics.