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Sci/Tech

Open Data for Genome Research: Multiplex Assays of Variant Effect (MAVE)

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OSS
Sci/Tech
  • New, open-source database improves genomics research collaboration

    Sharing datasets that reveal the function of genomic variants in health and disease has become easier, with the launch of a new, open-source database developed by Australian and North American researchers.

    The MaveDB database is a repository for data from experiments - called multiplex assays of variant effect (MAVEs) - that systematically measure the impact of thousands of individual sequence variants on a gene's function.

  • Open-source database enhances genomics research collaboration

    An open-source database of genomic variants in health and disease has been developed by Australian and North American researchers to simplify the sharing of this information between academics.

    The MaveDB database stores data from multiplex assays of variant effect (MAVE) experiments, which systematically measure the impact of thousands of individual sequence variants on a gene’s function. It was developed by researchers from the Walter and Eliza Hall Institute of Medical Research in Melbourne, Australia, as well as the University of Washington in the US and the University of Toronto in Canada.

  • Open-source Database Enhances Genomics Research Collaboration

    The MaveDB database is a repository for data from experiments – called multiplex assays of variant effect (MAVEs) – that systematically measure the impact of thousands of individual sequence variants on a gene’s function. These experiments can provide valuable information about how proteins produced by that gene function, how variants in that gene may contribute to disease, and how to engineer synthetic versions of naturally occurring proteins that are more effective than the original protein.

    MaveDB is the first publicly accessible database for this data. Its development was led by Alan Rubin from the Walter and Eliza Hall Institute, Australia, Associate Professor Douglas Fowler from the University of Washington, US, and Professor Frederick Roth from the University of Toronto, Canada.

Halloween Update for FreeCAD & Debian Science Work

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Debian
Sci/Tech

In August, a major milestone towards unified, mainline mechanical assembly functionality in FreeCAD was reached.

One of the core challenges in implementing assembly functionality is the problem of topological naming. In a CAD model there are topological entities, such as solids, faces, edges, and vertices. We must choose some algorithm to name them so that you can refer to relationships to make an assembly. A simple example would be two cubes, connected by touching faces. If a parameter in your model changes, and after recalculation, your "Face_N" is on the wrong side of the cube, your assembly may break, or not be what you are expecting. Without a good approach to topological naming, parametric FreeCAD models won't be robust to changes and recalculations, which defeats the purpose of parametric modeling.

Because this is such a difficult problem, progress has been slow. However, recently a relatively new FreeCAD developer, 'realthunder', put significant work towards this problem, with a solution finally on the horizon. Because it required major changes to FreeCAD's internals, the review and testing period was and continues to be lengthy.

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The UNIX OS – 50 years and counting

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OS
Sci/Tech

The UNIX OS design elements exist in numerous forms today, and its role in the evolution of computing is evident across entire infrastructures. Having enabled technologies such as cloud computing, security, virtualisation and mobility, it’s integral to the foundation of technologies ranging from cloud function as a service to serverless computing.

The Internet was built on the UNIX system in the 1970s, with the first world wide web server running on a UNIX system back in 1989. Sectors including manufacturing, government, healthcare and financial services have adopted it in huge numbers and its impact is still evidenced across numerous Fortune 100 companies today.

Modern-day examples include its use in the Human Genome Project as a platform to decode the human genome and as a render farm of UNIX systems in the first Disney-Pixar full length CGI animated film, Toy Story. Most of today’s ATMs and air traffic control platforms also run on UNIX derived systems, amongst numerous other examples of current implementations.

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Ada Lovelace Day: 5 Amazing Women in Tech

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Sci/Tech

It’s Ada Lovelace day and I’ve been lax in previous years about celebrating some of the talented women in technology I know or follow on the interwebs. So, to make up for it, here are 5 amazing technologists.

I was initially aware of Allison through her work on Perl, was vaguely aware of the fact she was working on Ubunutu, briefly overlapped with her at HPE (and thought it was impressive HP were hiring such high calibre of Free Software folk) when she was working on OpenStack, and have had the pleasure of meeting her in person due to the fact we both work on Debian. In the continuing theme of being able to do all things tech she’s currently studying a PhD at Cambridge (the real one), and has already written a fascinating paper about about the security misconceptions around virtual machines and containers. She’s also been doing things with home automation, properly, with local speech recognition rather than relying on any external assistant service (I will, eventually, find the time to follow her advice and try this out for myself).

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7 Good Open Source AI/Machine Learning Systems

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OSS
Sci/Tech

Artificial intelligence is taking over many sectors in technology in the last few years. Developers from all different backgrounds finally realized the opportunities AI an achieve for them regardless of their needs. And as usual in any new buzz, proprietary solutions are always developed to try to take a piece of the new market, but open source ones were also developed to allow everybody to have their share of the new technology.

In today’s article, we list 7 of the best open source AI/Machine learning systems.

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7 Great Linux Statistical Analysis Tools

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GNU
Linux
Software
Sci/Tech

Science is the effort of seeking to comprehend how the physical world works. From observation and experimentation, science uses physical evidence of natural phenomena to compile data and analyze the collated information.

In modern research it is essential for scientists to keep abreast of the latest statistical software. Just like the fast moving world of research, developments in statistical software and methods continue to abound. Making full use of the improvements in computer software helps to advance the pace of research.

Science really prospers and advances when individuals share the results of their experiments with others in the scientific community. There is a certain logic that scientific software should therefore be released in a freely distributable environment.

Linux is particularly strong in the field of open source statistical software. The purpose of this article is to identify software for performing statistical analysis. This type of software helps to summarize data in a shorter form, and helps scientists understand a concept or representation and make possible predictions based on this understanding.

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GNU Scientific Library 2.6 released

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GNU
Sci/Tech

Version 2.6 of the GNU Scientific Library (GSL) is now available. GSL provides a large collection of routines for numerical computing in C.
This release introduces major performance improvements to common linear algebra matrix factorizations, as well as numerous new features and bug fixes. The full NEWS file entry is appended below.
The file details for this release are:
ftp://ftp.gnu.org/gnu/gsl/gsl-2.6.tar.gz
ftp://ftp.gnu.org/gnu/gsl/gsl-2.6.tar.gz.sig
The GSL project homepage is http://www.gnu.org/software/gsl/
GSL is free software distributed under the GNU General Public License.
Thanks to everyone who reported bugs and contributed improvements.
Patrick Alken

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Cantor 19.08

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KDE
Sci/Tech

Since the last year the development in Cantor is keeping quite a good momentum. After many new features and stabilization work done in the 18.12 release, see this blog post for an overview, we continued to work on improving the application in 19.04. Today the release of KDE Applications 19.08, and with this of Cantor 19.08, was announced. Also in this release we concentrated mostly on improving the usability of Cantor and stabilizing the application. See the ChangeLog file for the full list of changes.

For new features targeting at the usability we want to mention the improved handling of the “backends”. As you know, Cantor serves as the front end to different open-source computer algebra systems and programming languages and requires these backends for the actual computation. The communication with the backends is handled via different plugins that are installed and loaded on demand. In the past, in case a plugin for a specific backend failed to initialize (e.g. because of the backend executable not found, etc.), we didn’t show it in the “Choose a Backend” dialog and the user was completely lost. Now we still don’t allow to create a worksheet for this backend, but we show the entry in the dialog together with a message about why the plugin is disabled.

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Gnuastro 0.10 released

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GNU
Sci/Tech

Dear all,

I am pleased to announce the 10th release of GNU Astronomy Utilities
(Gnuastro 0.10).

Gnuastro is an official GNU package of various command-line programs
and library functions for the manipulation and analysis of
(astronomical) data. All the programs share the same basic
command-line user interface (modeled on GNU Coreutils). For the full
list of Gnuastro's library, programs, and a comprehensive general
tutorial (recommended place to start using Gnuastro), please see the
links below respectively:

https://www.gnu.org/s/gnuastro/manual/html_node/Gnuastro-library.html
https://www.gnu.org/s/gnuastro/manual/html_node/Gnuastro-programs-list.html
https://www.gnu.org/s/gnuastro/manual/html_node/General-program-usage-tutorial.html

Many new features have been added, and many bugs have been fixed in
this release. For the full list, please see [1] below (part of the
NEWS file within the tarball). Some of the highlights are: 1) You can
now do column arithmetic (on FITS and plain text tables) directly
within the Table program, it also has some operators unique to table
columns for example conversion of pixel to world coordinate system
(WCS) coordinates and vice-versa. 2) Crop can now be used to pull out
sections of 3D data cubes also. 3) You can let CosmicCalculator find
the red-shift by identifying an emission line's wavelength or name,
and its observed wavelength.

Here is the compressed source and the GPG detached signature for this
release. To uncompress Lzip tarballs, see [2]. To check the validity
of the tarballs using the GPG detached signature see [3]:

  https://ftp.gnu.org/gnu/gnuastro/gnuastro-0.10.tar.gz     (5.2MB)
  https://ftp.gnu.org/gnu/gnuastro/gnuastro-0.10.tar.gz.sig (833B)
  https://ftp.gnu.org/gnu/gnuastro/gnuastro-0.10.tar.lz     (3.4MB)
  https://ftp.gnu.org/gnu/gnuastro/gnuastro-0.10.tar.lz.sig (833B)

Here are the MD5 and SHA1 checksums (other ways to check if the
tarball you download is what we distributed):

886c7badcd5b94d28bb616013b303bfb  gnuastro-0.10.tar.gz
48d1081543ba19b5d1b59e6d29b3b349  gnuastro-0.10.tar.lz
fce509583955f4bf15a764f30c7720de9df01a83  gnuastro-0.10.tar.gz
23c7f8d570e7b2851302500b5227026cb0d76340  gnuastro-0.10.tar.lz

For this release, I am very grateful to Alexey Dokuchaev, Joseph Putko
and Raul Infante-Sainz for direct contributions to Gnuastro's
source. Hamed Altafi, Roberto Baena Gallé, Zahra Bagheri, Leindert
Boogaard, Bruno Haible, Raul Infante-Sainz, Lee Kelvin, Elham Saremi,
Zahra Sharbaf, David Valls-Gabaud and Michael Wilkinson (in
alphabetical order) also provided very good suggestions and bug
reports, I am very grateful to them.

If any of Gnuastro's programs or libraries are useful in your work,
please cite _and_ acknowledge them. For citation and acknowledgment
guidelines, run the relevant programs with a `--cite' option (it can
be different for different programs). Citations _and_ acknowledgments
are vital for the continued work on Gnuastro, so please don't forget
to support us by doing so.

This tarball was bootstrapped (created) with the tools below. Note
that you don't need these to build Gnuastro from the tarball, these
are the tools that were used to make the tarball itself. They are only
mentioned here to be able to reproduce/recreate this tarball later.
  Texinfo 6.6
  Autoconf 2.69
  Automake 1.16.1
  Help2man 1.47.10
  ImageMagick 7.0.8-58
  Gnulib v0.1-2794-gc8e2eee54
  Autoconf archives v2019.01.06-55-gc5711b3


The dependencies to build Gnuastro from this tarball are described
here:
  https://www.gnu.org/s/gnuastro/manual/html_node/Dependencies.html

Best wishes,
Mohammad

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LabPlot has got some beautifying and lots of datasets

Filed under
KDE
Software
Sci/Tech

Hello everyone! The second part of this year's GSoC is almost over, so I was due to let you know the progress made in the last 3 weeks. I can assure you we haven't lazed since then. I think I managed to make quite good progress, so everything is going as planned, or I could say that even better. If you haven't read about this year's project or you just want to go through what has already been accomplished you can check out my previous post.

So let's just go through the new things step by step. I'll try to explain the respective feature, and also give examples using videos or screenshots.

The first step was to improve the welcome screen and make it easily usable, dynamic, clean and intuitive for users. This step was very important since the welcome screen is what the users will first get in contact with when they start using LabPlot.

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