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    Project admins: [Photo] Gary Van Domselaar
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    Submitter

    August 10-14, 2020
    Online
    www.transmittingscience.com/cour[...]udio/

    COURSE OVERVIEW

    This course will cover some advanced issues in most statistical computing workflow for Environmental Science. We will cover several aspects of data structure and workspace management, visualization techniques and statistical analysis using the free platforms and programming language R and Rstudio.

    The course is given in four modules covering exploratory data analysis, univariate and multivariate statistical techniques and a final discussion session where students will work and discuss their projects.

    REQUIREMENTS

    Graduate or postgraduate degree in Life Sciences and basic knowledge of Statistics and R.

    All participants must bring their own personal laptop and a good internet connection (Windows, Macintosh, Linux).

    July 14-17, 2020
    National Institutes of Health (ONLINE)
    faes.org/even[...]y2020

    OBJECTIVES

    Participants will get a brief introduction to the programming concepts, followed by hands-on walkthrough for writing scripts using the Unix Shell Programming Language, R, Perl and Python. We will start from reading the data, processing it and all the way until saving the processed data.

    BACKGROUND

    Computer programs are meant to perform repeated, monotonous, fast, reproducible tasks, handling any amount of data. Researchers often come across situations where existing programs don't suit their needs. In the era of BigData, without the ability to quickly put together a program that would solve their problem, researchers face a road block that is not efficiently solvable by a human. This training will walk through participants in writing programs that would help them solve their own problems.

    Simultaneous access to two screens is highly recommended for adequate learning experience. Examples include two laptops, one computer with two screens, one laptop and one tablet, etc.

    HIGHLIGHTS

    • Participants will work in a friendly Linux GUI Desktop environment.
    • Participants will get a copy of all the scripts used in the class.
    • Participants will also receive a cookbook style manual for all the hands-on exercises.
    Hands-on Skills/Tools Taught:
    • Programming concepts using Microbit MakeCode
    • Programming in Unix Shell Language
    • Programming in R using RStudio
    • Programming in Python using Jupyter
    • Programming in Perl
    • GitHub for version control
    • Serverless computing
    • Coding in the cloud

    Submitter

    Installing BLAST Databases on Your Own Computer:
    The BIRCH/BioLegato system provides easy point-and-click tools for installing, updating and searching BLAST databases on your own computer. This video describes some of the things you need to consider if you plan to install local copies of BLAST databases, including disk space and network download limits, and takes you through the automated install process.

    Video: youtu.be/R_gxDCXNUHY

    BLAST Searches Through a Data Science Lens:
    There's a lot more to BLAST searches than just running BLAST. We'll show how the BIRCH/BioLegato system implements Data Science principles to do database searches that are more informative, and to pipe your results directly into downstream analysis. Searches can be run either with copies of the databases installed on your computer, or by remote calls to BLAST at NCBI.

    Video: youtu.be/Os3eKqXF4Mw

    Submitter

    June 1-5, 2020
    Online
    www.physalia-courses.org/cour[...]se33/

    Due to the COVID-19 pandemic the Physalia course on "Metagenomics, metatranscriptomics, and multi'omics for microbial community studies" will be also held online.

    Instructors: Dr. Curtis Huttenhower, Dr. Jeremy E. Wilkinson, Dr. Kelsey N Thompson, Dr. Eric Franzosa (Department of Biostatistics, Harvard T.H. Chan School of Public Health)

    This course will provide a thorough introduction to microbial community data analysis (metagenomics, metatranscriptomics, and other culture-independent molecular data) through a balanced approach of lectures and hands-on lab sessions. Course participants will learn how to process data from raw meta'omic sequencing files through appropriate bioinformatic methods and approaches for subsequent integrative statistical analyses. Participants are invited to bring their own data to the practical session on the final day or can use publicly available data from the Integrative Human Microbiome Project (HMP2).

    Programme: www.physalia-courses.org/cour[...]m-33/

    All the Physalia courses will be held online until July: www.physalia-courses.org/courses-workshops/

    Should you have any questions, please contact us at info[at]physalia-courses.org

    November 15, 2020, 9am-5:30pm
    Georgia World Congress Center (GWCC), Atlanta, GA, USA
    To be held in conjunction with SC 2020
    works-workshop.org

    Scientific workflows have been almost universally used across scientific domains and have underpinned some of the most significant discoveries of the past several decades. Workflow management systems (WMSs) provide abstraction and automation which enable a broad range of researchers to easily define sophisticated computational processes and to then execute them efficiently on parallel and distributed computing systems. As workflows have been adopted by a number of scientific communities, they are becoming more complex and require more sophisticated workflow management capabilities. A workflow now can analyze terabyte-scale data sets, be composed of one million individual tasks, require coordination between heterogeneous tasks, manage tasks that execute for milliseconds to hours, and can process data streams, files, and data placed in object stores. The computations can be single core workloads, loosely coupled computations, or tightly all within a single workflow, and can run in dispersed computing platforms.

    This workshop focuses on the many facets of scientific workflow management systems, ranging from actual execution to service management and the coordination and optimization of data, service, and job dependencies. The workshop covers a broad range of issues in the scientific workflow lifecycle that include: scientific workflows representation and enactment; workflow scheduling techniques to optimize the execution of the workflow on heterogeneous infrastructures; workflow enactment engines that need to deal with failures in the application and execution environment; and a number of computer science problems related to scientific workflows such as semantic technologies, compiler methods, scheduling and fault detection and tolerance.

    IMPORTANT DATES

    Full paper deadline: August 15, 2020
    Paper acceptance notification: September 15, 2020
    E-copyright registration completed by authors: October 1, 2020
    Camera-ready deadline: October 1, 2020
    Workshop: November 15, 2020

    SUBMISSION GUIDELINES

    Full submission will be up to 8 pages long including references. All submitted papers will undergo a rigorous review process and each will have at least three reviews by members of the program committee. Papers will be accepted based on their technical contributions.
    Software: BIRCH Bioinformatics System 3.60
    Submitted by Brian Fristensky; posted on Wednesday, April 29, 2020

    Submitter

    NEW

    • First time setup tutorial for MATE desktop
    • Python3 compliance
    • Updates to BLAST, FASTA database searches

    BIRCH IS

    • A comprehensive desktop bioinformatics system which comes with many of the commonly-used bioinformatics programs pre-installed
    • A framework of tools, files, and documentation for organizing and managing a bioinformatics core facility
    • An expandable system that allows you to merge 3rd party programs and documentation seamlessly into the standard BIRCH distribution
    Download BIRCH at home.cc.umanitoba.ca/~psg[...].html

    Visit our YouTube Channel at www.youtube.com/chan[...]ublic

    November 18-22, 2020
    Bangkok, Thailand
    iconip2020.apnns.org

    The 27th International Conference on Neural Information Processing (ICONIP2020) aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progresses and achievements.

    ICONIP2020 will be collocated with several events, including ACML, iSAI-NLP, JIST-KG, and AIoT.

    TOPICS

    ICONIP2020 will deliver keynote speeches, invited talks, full paper presentations, posters, tutorials, workshops, social events, etc. Topics include but are not limited to:
    • Theory and Algorithms
    • Computational and Cognitive Neurosciences
    • Human Centered Computing
    • Applications

    IMPORTANT DATES

    Paper Submission Deadline: May 1, 2020
    Paper Notification Date: August 15, 2020
    Paper Camera-Ready Deadline: September 15, 2020

    Tutorial Proposal Deadline: May 1, 2020
    Tutorial Proposal Notification Date: May 8, 2020
    Tutorial Material/Website Deadline: September 15, 2020
    Tutorials Date: Nov. 18, 2020

    Workshops/Special Sessions Proposal Deadline: May 1, 2020
    Workshops/Special Sessions Proposal Notification Date: May 8, 2020
    Workshops/Special Sessions Material/Website Deadline: September 15, 2020
    Workshops/Special Sessions Date: Nov. 18, 2020

    PAPER INFORMATION

    Papers should be written in English and follow the Springer LNCS format. Paper submissions are single-blind review, so author names can be shown in the submission. The submission of a paper implies that the paper is original and has not been submitted under review or is not copyright-protected elsewhere and will be presented by an author if accepted. All submitted papers will be refereed by experts in the field based on the criteria of originality, significance, quality, and clarity.

    The Proceedings will be published in the Springer's series of Lecture Notes in Computer Science. Selected papers will be reviewed and published in some special issues of SCI journals.

    Final papers after acceptance will normally be 10 pages with a maximum of 12 pages in length. The page count includes everything, including references and appendices. Please follow Springer's proceedings LaTeX templates provided in Overleaf (www.overleaf.com/late[...]5uZpi).

    Submission site: cmt3.research.microsoft.com/User[...]p2020

    Submitter

    FirstGlance in Jmol (firstglance.jmol.org – or google firstglance as one word (no space) – free and open source) provides guided macromolecular visualization with remarkable ease of use and extensive help. Designed for educators and students, nevertheless it has ample power for researchers. Non-technical language abounds. For example, the B-factor/temperature color scheme is labeled "Local Uncertainty" (with the technical terms in the explanation). Resolution, reliability, asymmetric unit, biological assembly, etc. are explained in plain language. Any view can be easily saved as a rocking animation for presentation slides or websites (tinyurl.com/movingmolecules).
    • The name "FirstGlance" refers to a maximally informative initial view. Each chain is a distinct pastel color. Missing residues are marked with "empty baskets" so you won't be unaware (examples: 6NJE firstglance.jmol.org/fg.htm?mol=6nje and 2ho3 firstglance.jmol.org/fg.htm?mol=2ho3). Missing sidechains are labeled "S-", D-amino acids "D", non-standard residues "X". Full names of ligands are listed, clickable to locate each in the 3D structure.
    • Fundamental features such as secondary structure, distributions of hydrophobic/polar residues and charges, disulfide bonds, salt bridges, cation-pi interactions and more can be seen with one click each. Color keys and help appear automatically. All protein-protein salt bridges (including those involving ends of protein chains) can be listed, spreadsheet ready (example listing bioinformatics.org/firs[...]s.htm for 1HXW firstglance.jmol.org/fg.htm?mol=1hxw).
    • Components of a structure can be hidden to simplify the view, just by clicking on them. They remain hidden in all other views until explicitly re-displayed.
    • Any single chain or compound, or range of residues, can be isolated (everything else hidden) with one or a few clicks.
    • A powerful "Find" mechanism highlights short sequences, ranges of sequence numbers, residues by name, chemical elements, etc. Contacts and non-covalent bonds with whatever you find are easily displayed. Found items can be isolated or hidden.
    • You can select any component and then see what is non-covalently (or covalently) bound to it in just a few clicks. Seven categories of non-covalent interactions with your designated target can be shown, one at a time.
    • Reliability (Rfree) is objectively graded and explained. Date of publication, resolution, sequences, source organisms, molecular mass, chemical elements in the model, publication abstract are readily viewed. For the more advanced user, alternate locations can be animated with a few clicks (example: 2AGT firstglance.jmol.org/fg.htm?mol=2agt – click on alternate locations in the Introduction), occupancies less than 100% are summarized and easily located, and regions of the asymmetric unit with crystal contacts can be colored.
    FirstGlance is used about 300 times/day.

    I'm always interested in feedback, problems, bug reports, suggestions or questions.

    Eric Martz, Professor Emeritus, Dept Microbiology (he/him/his) U Mass, Amherst – Martz.MolviZ.Org

    Submitter

    Allison Proffitt at Bio-IT World is compiling a list of organizations that are providing free use of their resources to scientists involved in coronavirus research: www.bio-itworld.com/2020[...].aspx.

    Submitter

    May 18-22, 2020
    Free University (FU) Berlin, Germany
    www.physalia-courses.org/cour[...]rse9/

    INSTRUCTORS

    Dr. Martin Taylor and Dr. Lewis Spurgin (University of East Anglia, UK)

    COURSE OVERVIEW

    Next generation sequencing has revolutionized evolutionary biology allowing unprecedented resolution and insight into evolutionary questions that appeared intractable only a few years ago. The course will cover the basics of population genomic analysis from SNP data onwards and will cover the key analyses that may be required to successfully analyze a population genetic data set. The course will NOT cover steps prior to generation of a .vcf file or SNP data set such as NGS data demultiplexing, clustering and SNP calling (This is covered in detail in the Introduction to RADseq course). This course will introduce Linux and the command line environment, basic perl and python usage, file conversions and manipulation, population structure and differentiation in R, outlier analysis, landscape / seascape genomics and introgression. Having completed the course, students should have a good understanding of the software and methods available for population genomic analysis and be competent in population genomic analysis.

    TARGETED AUDIENCE & ASSUMED BACKGROUND

    This course is aimed at postgraduate students and early career researchers who are interested in using population genomic tools in their research. No previous experience of bioinformatics is required, but an underpinning in evolutionary biology and basic population genetics concepts such as Hardy Weinberg Equilibrium and FST are desirable. The course will use a range of software including the Linux operating system and R.

    Program: www.physalia-courses.org/cour[...]lum9/

    Here is the full list of our courses and Workshops: www.physalia-courses.org/courses-workshops/
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