Aims and scope

BMC Bioinformatics is an open access, peer-reviewed journal that considers articles describing novel computational algorithms and software, models and tools, including statistical methods, machine learning and artificial intelligence, as well as systems biology.

BMC Bioinformatics does not make editorial decisions on the basis of the interest of a study or its likely impact. Studies must be scientifically valid; for research articles this includes a scientifically sound research question, the use of suitable methods and analysis, and following community-agreed standards relevant to the research field.

Special Issue on Bioinformatics ethics and data privacy
截稿日期: 2024-12-13

Guest Editor

Vasiliki Rahimzadeh, PhD, Center for Medical Ethics and Health Policy, Baylor College of Medicine, USA

BMC Bioinformatics is calling for submissions to our Collection on Bioinformatics ethics and data privacy. 

The amount of biological data stored on both local storage systems and online platforms and databases is as large as ever. With the constant increase in the use of data for both digital health and research purposes, ethics and data privacy are important consideration in this increasingly digital world. Matters such as the implications for future generations of storing genetic information, transparency when it comes to consent, human bias when handling data and considerations on benefits versus risks of storing certain types of information are some examples. Solutions for and conversations about cyber security and local storage vs online databases come into play.

This Collection welcomes submissions on new computational approaches, tools, and databases to address issues and open questions in bioinformatics ethics and data privacy, including anonymization, encryption and data deposition.

In alignment with the United Nations Sustainable Development Goal SDG 16, which seeks to promote just, peaceful, and inclusive societies, this collection emphasizes the importance of respecting and upholding the right to privacy and access to information.

Special Issue on Computational methods in microscopy image analysis
截稿日期: 2025-02-27

Guest Editor

Dariusz Plewczyński, PhD, Warsaw University of Technology, Poland

BMC Bioinformatics is welcoming submissions for our Collection focused on Computational methods in microscopy image analysis.

Microscopy imaging techniques have revolutionized our understanding of biological processes by enabling the visualization of cellular and molecular details with unprecedented resolution. However, the complexity and volume of microscopic data pose significant challenges for analysis and interpretation. Computational methods are crucial in extracting meaningful information from microscopy images, enhancing image resolution, and uncovering subtle biological processes.

This Collection aims to showcase innovative computational approaches and bioinformatics tools tailored for microscopy image analysis, with potential topics including but not limited to:

    Computational methods in Electron Microscopy and FRET-FLIM microscopy
    Image processing techniques for light microscopy and confocal microscopy
    Novel algorithms for image segmentation, object detection, and feature extraction in microscopy
    Integration of multi-modal and SCAPE microscopy data
    Quantification of spatial and temporal dynamics in fluorescence microscopy analysis
    Convolution and deconvolution methods for microscopy images
    Application of machine learning techniques for automated microscopy image analysis

This Collection supports and amplifies research related to SDG 9: Industry, Innovation, and Infrastructure.

Special Issue on Bioinformatics in agriculture
截稿日期: 2025-03-14

Guest Editors

Ratna Prabha, PhD, Agricultural Knowledge Management Unit, ICAR-Indian Agricultural Research Institute, India
Anil Rai, PhD , Master in Computer Applications, Indian Council of Agricultural Research, India

BMC Bioinformatics is welcoming submissions to our Collection focused on Bioinformatics in agriculture. Bioinformatics is gaining an increasingly prominent role in the field of agriculture and plays a crucial role in precision farming and sustainable agriculture practices. Agri-informatics integrates bioinformatics tools and computational methods to analyze agricultural data, ranging from plant genome mapping to agricultural big data analytics. By leveraging advanced bioinformatics techniques, researchers can enhance crop productivity, mitigate crop diseases, and optimize resource management in agriculture.

This Collection aims to showcase innovative research in agricultural bioinformatics and welcomes submissions on novel computational and statistical approaches in the field of agriculture.

Potential topics include, but are not limited to, computational and statistical approaches for:

    Crop genome mapping and annotation
    Analysis and interpretation of agricultural big data
    Genetic variants associated with crop stress tolerance
    Agri-informatics platforms for precision farming, crop monitoring, and yield prediction
    Analysis of pathogen-plant interactions and development of disease-resistant crops
    Computational modeling and simulation of crop growth
    Machine learning and artificial intelligence techniques in plant breeding analytics and crop trait prediction

Special Issue on Microbial taxonomy
截稿日期: 2025-03-27

Guest Editors

Xiaoquan Su, PhD, Qingdao University, China
Yanni Sun, PhD, City University of Hong Kong, China

BMC Bioinformatics is welcoming submissions to our Collection on Microbial taxonomy.

Microbial taxonomy is the identification, classification and nomenclature of microorganisms, providing a framework to understand microbial diversity and their ecological roles. Computational tools have widely been employed for taxonomic classification, for example in the context of binning and metagenomic analysis, as well as database construction. 

This Collection welcomes submissions on the development of novel computational and statistical approaches in the field of microbial taxonomy, as well as major advancements of existing tools. New microbial taxonomy databases which describe a novel architecture, set-up or bioinformatics analysis are also welcome. 

Special Issue on Eukaryotic phylogenetics
截稿日期: 2025-04-16

Guest Editors

Jijun Tang, PhD, Shenzhen University of Advanced Technology, China
Dapeng Wang, PhD, Imperial College London, UK

BMC Bioinformatics is welcoming submissions to our Collection on Eukaryotic phylogenetics.
 
Eukaryotic phylogenetics explores the evolutionary relationships between and diversification of eukaryotic organisms based on morphological data and molecular sequence data, providing insights into their genetic diversity and evolutionary history. Computational approaches have been widely used in the phylogenetics field, proving especially useful in this era of omics and increasingly large datasets.
 
This Collection welcomes submission on computational and statistical methods for the study of eukaryotic phylogenetics, including both alignment-based and alignment-free approaches, new databases and visualisation tools for eukaryotic phylogenetic trees. Computational and statistical approaches for the integration, automation and standardization of large-scale phylogenetic and phylogenomic analysis are also welcome.