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    Resources: Computational resources in health care
    Submitted by Gajendra P.S. Raghava; posted on Wednesday, November 17, 2021

    Submitter

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

    Submitter

    March 17-18, 2022
    Grand Hotel Mediterraneo
    Florence, Italy, and online
    conference.pixel-online.net/NPSE[...]s.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.

    IMPORTANT DATES

    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.

    FOR MORE INFORMATION

    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.

    Submitter

    Proteome-pI 2.0 (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 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 www.isoelectricpointdb2.org/download.html).

    AVAILABILITY

    The database is available at www.isoelectricpointdb2.org and isoelectricpointdb2.mimuw.edu.pl (mirror)

    REFERENCE

    Kozlowski LP. Proteome-pI 2.0: Proteome Isoelectric Point Database Update. Nucleic Acids Res. 2021 (Database Issue), doi: dx.doi.org/10.1093/nar/gkab944

    Submitter

    ABSTRACT EXCERPT

    The knowledge of the history of a subject stimulates understanding. As we study how other people have made scientific breakthroughs, we develop the breadth of imagination that would inspire us to make new discoveries of our own. This perspective certainly applies to the teaching of genetics as hallmarked by the pea experiments of Mendel. Common questions students have in reading Mendel's paper for the first time is how it compares to other botanical, agricultural, and biological texts from the early and mid-nineteenth centuries; and, more precisely, how Mendel's approach to, and terminology for debating, topics of heredity compare to those of his contemporaries?
    Article: doi.org/10.1[...]308-4
    Citation: Poczai, P., Santiago-Blay, J.A. Principles and biological concepts of heredity before Mendel. Biol Direct 16, 19 (2021).
    Resources: Predict protein structure from sequence easily, free!
    Submitted by Eric Martz; posted on Tuesday, October 26, 2021

    Submitter

    The AlphaFold project of DeepMind (Google) made a dramatic breakthrough in 2020. AlphaFold is often able to predict the structure of a protein from its sequence so well that the difference between the prediction and an X-ray crystallographic structure is as small as the difference between two independent X-ray determinations.

    Now, thanks to ColabFold, anyone can submit a sequence and get a free AlphaFold2 structure prediction. Its easy! Here are instructions:

    proteopedia.org/w/Ho[...]aFold

    Reliability is estimated for each amino acid. FirstGlance in Jmol now automatically colors AlphaFold/ColabFold predictions by estimated reliability. Upload your predicted PDB file to

    bioinformatics.org/firstglance/fgij

    Snapshot of Alphafold2 Colab prediction displayed in FirstGlance colored by estimated reliability per residue: bioinformatics.org/molv[...]d.png

    Examples of AlphaFold2 Colab predictions ready to view instantly in FirstGlance: bioinformatics.org/firs[...]s.htm

    Submitter

    Bioinformatics is a diverse and exciting field. Best described as data science for the life sciences, it uses computational approaches to extract meaningful information from complex data sets, providing novel insights in biological, clinical and environmental science. This rapidly-growing area of science is driving new discoveries for today's data-driven health and life science industries.

    To meet the growing demand for such expertise, the University of Birmingham has launched an innovative new programme – the Online MSc Bioinformatics (landing.birmingham.ac.uk/uob/[...]ept21).

    Designed to bridge expertise in both data and life sciences in order to enable the best tools to analyse the best data, the programme is delivered 100% online. Combining different fields of study, including computer sciences, molecular biology, biotechnology, statistics, machine learning and engineering, it seeks to appeal to biologists and healthcare professionals interested in data analysis, as well as statisticians, computer or data scientists wishing to apply their skills in biology.

    Expertly adapted for online audiences from the campus-based programme, which is ranked top-20 in the UK for both Biology and Computer Science by QS 2021, the curriculum is delivered by the Centre for Computational Biology – a cross-campus initiative providing broad expertise in data science for the life sciences through both research and training – the programme is uniquely placed to support those eager to get ahead in this invaluable industry.

    Led by industry renowned Professor of Bioinformatics, Prof Jean-Baptiste Cazier – founder and designer of both the Centre for Computational Biology and the campus Bioinformatics MSc – students will learn to communicate effectively with fellow biologists, computer scientists and statisticians, interact with complex data sets, learn and teach with data and improve their coding skills.

    Applications are now open for the February 2022 intake – request more information (landing.birmingham.ac.uk/uob/[...]ept21) to find out how to apply today.
    Events: Health Informatics Summit
    Submitted by Gajendra P.S. Raghava; posted on Thursday, September 02, 2021

    Submitter

    October 16-19, 2021
    Indraprastha Institute of Information Technology (IIIT-D)
    Delhi, India
    webs.iiitd.edu.in/hitsummit/

    Department of Computational Biology at Indraprastha Institute of Information Technology (IIIT-D), Delhi in association with APBians is organizing a "Health Informatics Summit" from 16-19 October 2021. No registration fees required. For more information, please visit the website.

    Submitter

    A new version of FirstGlance in Jmol FirstGlance.Jmol.Org (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.

    This new version should help to de-mystify electron density maps by making them super easy to look at – both for X-ray, and for Electron Microscopic Coulombic density maps. You simply "Find" a few residues (click "Find.." in the Focus Box and, for example, with 1ijw enter Ser174,DA10) which identifies them with yellow halos, whereupon the density map is just one more click. See slides 5-6 showing FirstGlance-generated animations of density maps at tinyurl.com/movingmolecules. For educators and students, this new version starts up in a simplified mode, with fewer details cluttering the Molecule Information Tab and hiding advanced tools in the Tools tab. Still, much is offered about the model, including reliability (Rfree interpreted for you), number of chains and which are sequence-identical, sequences, missing residues, full names of ligands, and the biological assembly. The Views Tab shows secondary structure, hydrophobic cores, charge distribution, etc. The Tools Tab shows protein crosslinks, ends of chains, salt bridges, cation-pi interactions, and non-covalent interactions with any moiety you specify.

    Click "Show More Details" only if you want detailed analyses of alternate locations (which can be animated) and occupancies, counts of incomplete sidechains, various protein crosslinks, related PDB entries, one-click access to view the PDB data file contents, coloring by temperature/B factor, etc.

    This version automatically detects likely cases of the following covalent protein crosslinks (in addition to disulfide bonds, already in FirstGlance for years): isopeptide crosslinks, thioester crosslinks, thioether crosslinks, ester crosslinks, His-Tyr crosslinks, and Lys-Cys NOS crosslinks (first reported a few months ago). Clicking on one crosslink zooms in and shows it in detail, with the electron density map being one further click. Thanks to Amr A. Alhossary for finding some of the examples. Feedback always welcome!
    Software: Genozip: A universal compressor for genomic files
    Submitted by Divon Lan; posted on Tuesday, July 20, 2021

    Genozip is a universal compressor for genomic files – it is optimized to compress FASTQ, SAM/BAM/CRAM, VCF/BCF, FASTA, GVF, PHYLIP, Chain, Kraken and 23andMe files, but it can also compress any other file (including non-genomic files).

    Typically, a 2X-5X improvement over the existing compression is achieved when compressing already-compressed files like .fastq.gz .bam vcf.gz, and up to 200X for a high-sample-count VCF file.

    Yes, Genozip can compress already-compressed files (.gz .bz2 .xz .bam .cram).

    The compression is lossless – the decompressed file is 100% identical to the original file.

    Details: genozip.com. Available on conda (conda-forge channel) and github.com/divonlan/genozip

    Reference:
    Lan, D., et al. (2021) Genozip: a universal extensible genomic data compressor Bioinformatics, btab102, doi.org/10.1[...]ab102

    Submitter

    ABSTRACT

    The literature knowledge panels developed and implemented in PubChem are described. These help to uncover and summarize important relationships between chemicals, genes, proteins, and diseases by analyzing co-occurrences of terms in biomedical literature abstracts. Named entities in PubMed records are matched with chemical names in PubChem, disease names in Medical Subject Headings (MeSH), and gene/protein names in popular gene/protein information resources, and the most closely related entities are identified using statistical analysis and relevance-based sampling. Knowledge panels for the co-occurrence of chemical, disease, and gene/protein entities are included in PubChem Compound, Protein, and Gene pages, summarizing these in a compact form. Statistical methods for removing redundancy and estimating relevance scores are discussed, along with benefits and pitfalls of relying on automated (i.e., not human-curated) methods operating on data from multiple heterogeneous sources.

    Full article: www.frontiersin.org/arti[...]/full
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