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    Louisiana State University LSU Official Mike The Fighting Tiger Archive Subscribe

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    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 (https://bit.ly/34rUQIy).
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    Submitted by J.W. Bizzaro; posted on Tuesday, February 08, 2022

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    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.
    Source: https://news.mit.edu/2022/ai-predicts-protein-docking-0201
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    Submitted by J.W. Bizzaro; posted on Monday, January 31, 2022

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    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 (https://bit.ly/3GsI4GJ). The postgraduate programme has three intakes per year – request more information to find out how to apply.
    Research: SciTechDaily: Videogame players needed to solve puzzles and help advance cancer research
    Submitted by J.W. Bizzaro; posted on Sunday, January 30, 2022
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    The game was created to boost worldwide research efforts that depend on cancer cell lines, a critical resource used by scientists to study cancer and test new drugs to treat the disease. One of the limitations of cancer cell lines are a lack of high-resolution genome reference maps, which are necessary to help researchers interpret their scientific results, for example pinpointing the location of genes of therapeutic interest or potential mutation sites.
    Source: https://scitechdaily.com/videogame-players-needed-to-solve-puzzles-and-help-advance-cancer-research/

    Game website: https://genigmagame.app/en/

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    Using the Nanoscale Molecular Dynamics, or NAMD, code on Summit, the nation's most powerful supercomputer, the researchers simulated the spike proteins' molecular structures for SARS-CoV-2 and three other human coronaviruses: SARS-CoV-1, MERS-CoV and HCoV-HKU1. After completing this unique and comprehensive comparison of four different spike proteins, they compared the components and behavior of SARS-CoV-2 with thousands of sample structures from the other viruses using a deep learning architecture called a convolutional variational autoencoder, or CVAE.

    These efforts revealed previously unexplored regions of the coronavirus's spike protein in which targeted medical intervention might prevent SARS-CoV-2 from infecting healthy cells.
    Source: https://www.ornl.gov/news/supercomputing-exposes-potential-pathways-inhibiting-covid-19
    Software: Evolutionary conservation of key amino acids more easily seen
    Submitted by Eric Martz; posted on Tuesday, January 25, 2022


    FirstGlance in Jmol http://bioinformatics.org/firstglance (free and open source as always) provides guided visual exploration of macromolecular structures with remarkable ease of use (no command language needed). The "FirstGlance" it offers is maximally informative. It alerts you automatically to missing residues (quite common in X-ray crystallographic models), incomplete sidechains, and unusual components or features including unusual covalent protein crosslinks (such as thioester or lysine-cysteine NOS bonds).

    Since 2006, FirstGlance has provided visualization of evolutionary conservation, calculated by the ConSurf Server http://consurf.tau.ac.il, coloring each amino acid in a protein structure by conservation level. All of ConSurf's state-of-the-art algorithms are published in peer-reviewed journals. Using ConSurf is easy. It gathers sequences, aligns them into a multiple protein sequence alignment (MSA), calculates conservation values, and colors your protein structure – all automatically. When the MSA provides inadequate information for a particular residue (large confidence interval), it is colored yellow for "insufficient data".

    This new version of FirstGlance optimizes zooming in on key residues and coloring them by evolutionary conservation. "One click (or a few)" tools do this for any residues that you specify, disulfide bonds, six other kinds of covalent protein crosslinks (e.g. isopeptide bonds), all salt bridges, all cation-pi interactions, and residues contacting any ligand or other substructure that you specify. You can toggle between coloring the atoms by chemical element or evolutionary conservation, provided that the protein structure model (PDB file) has been processed by ConSurf beforehand.

    Quick example for isopeptide and thioester crosslinks in FirstGlance: Here are some illustrated practical guides: Feedback always welcome!

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    The OneZoom explorer – available at https://onezoom.org – maps the connections between 2.2 million living species, the closest thing yet to a single view of all species known to science.

    The interactive tree of life allows users to zoom in to any species and explore its relationships with others, in a seamless visualisation on a single web page. The explorer also includes images of over 85,000 species, plus, where known, their vulnerability to extinction.
    Source: https://www.imperial.ac.uk/news/232634/visually-stunning-tree-known-life-unveiled/
    Resources: Computational resources in health care
    Submitted by Gajendra P.S. Raghava; posted on Wednesday, November 17, 2021


    We are pleased to share our list of computational resources in health care. It covers a wide range of informatics-based fields like chemoinformatics, medical informatics, pharmacoinformatics and bioinformatics. The paper and server are available from the following links.

    Paper link: https://doi.org/10.1002/widm.1437
    Web server: https://webs.iiitd.edu.in


    March 17-18, 2022
    Grand Hotel Mediterraneo
    Florence, Italy, and online
    http://conference.pixel-online.net/NPSE/callforpapers.php

    11th Edition – Hybrid Event

    The Conference brings together teachers, researchers, practitioners and project managers from all over the world to share findings, expertise and experience about innovative science teaching and learning methodologies, through on-site and on-line presentations, and social events.

    We will deliver a full 2 days programme of inspiring sessions in the framework of a highly interactive hybrid conference experience. We will provide enhanced contents that will give participants greater access to learning, sharing and networking.
    • All accepted papers at the conference will be presented on-site and on-line.
    • Interactive questions and answers sessions will follow each paper presentation.
    • On-site and on-line poster presentation sessions will also be held.
    • Networking opportunities will be organized.
    All accepted papers will be included in the Conference Proceedings published with ISBN, ISSN and DOI codes.

    The publication will be sent to be reviewed for inclusion in the Conference Proceedings Citation Index by Thomson Reuters (ISI-Clarivate). The publication will also be included in Academia and indexed in Google Scholar.
    Extended abstract submission deadline: November 17, 2021
    Notification of abstract evaluation: December 1, 2021
    Deadline for paper submission: January 21, 2022
    Conference days: March 17-18, 2022

    There will be five presentation modalities: oral and poster presentation on-site; oral, poster and asynchronous presentation on-line.
    Contact: science[at]pixel-online.net

    Health and Safety issues in relation to COVID-19:
    In case participants are not able to attend on-site, online, interactive, attendance/presentation opportunities are available. Participants attending/presenting online will benefit of a discounted fee. Every precaution possible is taken to create a safe environment for participants attending on-site (masks, gloves, distance seating, disinfection etc.). Finally, should the conditions do not allow the conference to be held on-site as expected, the event will shift to a fully virtual format.


    Proteome-pI 2.0 (http://www.isoelectricpointdb2.org) is an updated version of an online database containing information about predicted isoelectric points.

    The isoelectric point, the pH at which a particular molecule carries no net electrical charge, is an important parameter for many analytical biochemistry and proteomics techniques, especially for 2D gel electrophoresis (2D-PAGE), capillary isoelectric focusing, liquid chromatography-mass spectrometry, and X-ray protein crystallography.

    The following changes have been introduced:
    • The number of proteomes included has been increased four-fold (from 5,029 to 20,115)
    • New algorithms for isoelectric point prediction have been added (21 algorithms in total)
    • The prediction of pKa dissociation constants for over 61 million proteins have been included (5.38 Billion predictions in total)
    • The prediction of isoelectric point for in silico digests of proteomes with the five most commonly used proteases (trypsin, chymotrypsin, trypsin+LysC, LysN, ArgC) have been added (9.58 Billion peptides)
    The database allows the retrieval of virtual 2D-PAGE plots and the development of customized fractions of proteome based on isoelectric point and molecular weight.

    Moreover, Proteome-pI 2.0 facilitates statistical comparisons of the various prediction methods as well as biological investigation of protein isoelectric point space in all kingdoms of life (updated statistics available at http://www.isoelectricpointdb2.org/statistics.html). The database includes various statistics and tools for interactive browsing, searching, and sorting. It can be searched and browsed by organism name, average isoelectric point, molecular weight, or amino acid frequencies. Proteins with extreme pI values are also available. For individual proteomes, users can retrieve proteins of interest given the method, isoelectric point, and molecular weight ranges (this particular feature can be highly useful to limit potential targets in the analysis of 2DPAGE gels or before conducting mass spectrometry).

    Finally, some general statistics (total number of proteins, amino acids, average sequence length, amino acid, and di-amino acid frequencies) and datasets corresponding to major protein databases such as UniProtKB/TrEMBL and the NCBI non-redundant (nr) database have also been precalculated (see http://www.isoelectricpointdb2.org/download.html).
    The database is available at http://www.isoelectricpointdb2.org and http://isoelectricpointdb2.mimuw.edu.pl (mirror)
    Kozlowski LP. Proteome-pI 2.0: Proteome Isoelectric Point Database Update. Nucleic Acids Res. 2021 (Database Issue), doi: https://dx.doi.org/10.1093/nar/gkab944
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