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    August 7-9, 2022
    Philadelphia, PA, USA

    Dear Colleagues:

    The 10th International Conference on Intelligent Biology and Medicine (ICIBM 2022) will take place Philadelphia, PA, USA August 7-9, 2022, ICIBM is a high caliber conference which brings together eminent scholars with expertise in various fields of computational biology, systems biology, computational medicine, as well as experimentalists interested in application of computational methods in biomedical studies. The purpose of the ICIBM is to provide a congenial atmosphere highly conducive to extensive discussion and networking.

    Our keynote include Drs. Xihong Lin, Ludmil Alexandrov, Smita Krishnaswamy, Mona Singh. Eminent Scholars includes:Drs. Feixiong Cheng, Jiang Qian, Yuan Luo, Li Shen, Derrick Scott, Lana Garmire.

    Registration is open. Please join us.

    ICIBM 2022 Organization Committee

    The web service Hiplot has been published in the journal Briefings in Bioinformatics.


    Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud-and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (, with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multiuser plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.


    Jianfeng Li et al. "Hiplot: a comprehensive and easy-to-use web service for boosting the publication-ready biomedical data visualization." Briefings in Bioinformatics, bbac261 (2022).




    We are happy to announce a new web server and standalone software, HLAncPred, developed for predicting non-classical HLA binders.

    Web server link:

    Paper link:


    December 6-9, 2022
    International Conference on Bioinformatics and Biomedicine (BIBM 2022)
    Las Vegas, NV, USA

    Network Science and Artificial Intelligence for Biomedicine & Health informatics (NSAIBHI) Workshop:
    Network Science is a new paradigm of study to understand complex systems including biological interactions. Pharmacology and drug discovery leverage network biology advances for a better understanding of the complex interactions between drugs, targets and disease, for designing new molecule, and for identifying drugs to be successfully repurposed. More recently, graph neural networks expressed to be a potential game changer in deciphering the inherent complex interaction patterns in complex networks.

    The workshop and the foreseen special issue intend to highlight novel research in the area of network science, network biology and network medicine coupled with representation learning and its application to biology, medicine, and pharmacology. The focus is on, but not limited to, the following broad areas:

    1. Network Representation Learning
    2. Graph Convolution Neural Network
    3. Network Embedding
    4. Heterogeneous network integration
    5. Network Alignment
    6. Disease module detection
    7. Network Drug Discovery and Repurposing


    Electronic submission of full papers: Aug, 21, 2022
    Notification of paper acceptance: Oct 21, 2022
    Main conference Camera-ready of accepted papers: Nov 12, 2022
    Workshop Paper Camera-ready of accepted papers: Nov 12, 2022
    Conference: Dec. 6-9, 2022


    All workshop accepted papers and posters will appear in the IEEE Conference Proceedings.

    A special issue on a Scopus Indexed Journal is planned, negotiations are in progress, journals will be communicated in an upcoming announcement.
    Software: BIRCH Bioinformatics System v3.86
    Submitted by Brian Fristensky; posted on Saturday, June 11, 2022


    BIRCH 3.86 now available for download at


    • Important fix to OSX BIRCH launcher
    • Sequence database search improvements
    • Application updates
    BIRCH unifies hundreds of popular bioinformatics tools through the BioLegato family of Object-Oriented applications. BioLegato makes it easy to try out new programs, and to experiment with your data at every step in the analytical process.

    Visit our YouTube Channel at


    Healthcare is generating and collecting huge amounts of data from electronic health record systems, medical imaging, lab data and genomics testing. Tools and methods are currently being developed to improve our ability to analyze and understand this abundant amount of health data. Through the correct application of tools and methods, we can improve patient outcomes and reduce costs. Professionals with this ability are increasingly in high demand.

    The mission of Georgetown University's Health Informatics and Data Science program ( is to equip our students with cutting-edge techniques, to give them a firm grasp on methodologies and to be highly qualified for the market. It is designed to help students develop core competencies in data science, health-related data, predictive analytics, machine learning (ML), Artificial Intelligence (AI) and other advanced technologies. Through the program, students will be prepared to successfully take on a wide range of opportunities in health care organizations and related industries including, health technology developers, device manufacturers, pharma/biotech, academic medical centers and management consulting firms. We help our students build critical skills for this growing sector to lead the evolution of healthcare.

    Through multi-disciplinary coursework and projects, HIDS students will be exposed to, and interact with, field experts, peers and faculty from top-ranked Georgetown University departments. Our unique Georgetown experience prepares the next generation of health informaticians to lead and make a difference in patient care and population health.

    Make your career move now! Come talk to us about how Georgetown's Health Informatics & Data Science fits into your academic and professional goals! Please visit

    Georgetown-HIDS is a proud member of the AI/ML Consortium to Advance Health Equity & Researcher Diversity (AIM-AHEAD) Program (

    June 13-15, 2022
    Hotel Le Méridien, 20 Sidney St, Cambridge, MA, USA

    We are pleased to announce that the registration for our training "Bioinformatics, Biostatistics and Machine Learning Techniques for Biotech Applications" has been opened.

    If you want to learn about the latest techniques and applications of bioinformatics, statistics and ML in life science, you can find out more and register on the website listed above.

    During this 3-day hands-on training in Boston you will learn about:
    • NGS data analysis (Day 1)
    • Introduction to Biostatistics of Clinical Trials (Day 2)
    • Machine Learning (Day 3)
    Takeaway: You will learn about the most in-demand bioinformatics, biostatistics and machine learning techniques you need to succeed as a bioinformatician or data scientist in the biotech industry. For each pipeline and model, you will learn how it works conceptually first, then apply it to a particular industrial application, and finally learn to analyze and visualize the results.

    Registration: Secure your spot now. Seats are limited, and we accept applicants on a first-come, first-served basis.


    There's a lot to be impressed about when considering a career in bioinformatics.

    First, it's one of the most multidisciplinary fields of science, merging not just computing and biology but also drawing on methods from mathematics, engineering, physics and chemistry.

    Second, bioinformaticians are at the bleeding edge in applied computing, making use of artificial intelligence, Big Data and cloud computing to treat diseases and advance our understanding of life. In fact, many of the most powerful supercomputers in the world are used to solve bioinformatics problems.

    In the future, bioinformatics will bring personalized healthcare through the rapid and inexpensive analysis of a patient's whole genome, which can be ordered at their doctor's office. The future will also bring new therapies designed by artificial intelligence, cutting years off of development time.

    At the University of Birmingham you can be on your way to such an exciting and impactful career. Their flexible, 100% Online MSc Bioinformatics connects biology, clinical services, mathematics, and computer science, giving students the knowledge they need to respond to growing healthcare challenges.

    The university is now accepting Summer 2022 applications. Request more information to find out how to apply (



    Antibodies, small proteins produced by the immune system, can attach to specific parts of a virus to neutralize it. As scientists continue to battle SARS-CoV-2, the virus that causes Covid-19, one possible weapon is a synthetic antibody that binds with the virus' spike proteins to prevent the virus from entering a human cell.

    To develop a successful synthetic antibody, researchers must understand exactly how that attachment will happen. Proteins, with lumpy 3D structures containing many folds, can stick together in millions of combinations, so finding the right protein complex among almost countless candidates is extremely time-consuming.

    To streamline the process, MIT researchers created a machine-learning model that can directly predict the complex that will form when two proteins bind together. Their technique is between 80 and 500 times faster than state-of-the-art software methods, and often predicts protein structures that are closer to actual structures that have been observed experimentally.


    A new bioinformatics software and cloud computing approach developed at the University of Birmingham has enabled the UK's COVID-19 genome sequencing effort to be the most sophisticated in the world.

    CLIMB-COVID was designed for the COVID-19 Genomics UK (COG-UK) consortium, set up in March 2020 to tackle the huge challenge of rapidly sequencing SARS-CoV-2 genomes.

    The first version of CLIMB-COVID was designed and built by researchers at the University of Birmingham and Cardiff University in under a month and it has been crucial in processing the sequencing data of more than 675,000 coronavirus genomes, including identifying and tracking the Alpha and Delta variants that became dominant in the UK last year. The collaborative approach also integrates new software developed at the University of Edinburgh and the Centre for Genomic Pathogen Surveillance.

    The CLIMB-COVID system enables a distributed sequencing system which harnesses sequencing capability from universities, academic institutes and the UK's four public health agencies. The software and database infrastructure was able to receive all this data, process it and analyse it into interpretable outputs for public health analysts, helping to make the UK a world leader in sequencing the Coronavirus genome.

    All the data from the project has been integrated and shared in real-time. Not only has this enabled the UK's public health agencies to work together more effectively, but it also allowed seamless access and collaboration across academics, thereby helping to create and advance systems for the early detection and evaluation of new variants of the virus.

    You can be a part of the continuing advancements in bioscience at the University of Birmingham through the Online MSc Bioinformatics offered by the university ( The postgraduate programme has three intakes per year – request more information to find out how to apply.
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