The Open Bioinformatics Foundation (OBF) Event Fellowship program aims to promote diverse participation at events promoting open source bioinformatics software development and open science practices in the biological research community. Armando Blondel DJIYOU DJEUDA, a researcher from University of Douala, Cameroon, set up and host H3ABioNet‘s Introduction to Bioinformatics course (IBT), supported by this fellowship granted to him in application round 1 of 2020.

Due to the rich biodiversity of sub-Saharan African countries, bioinformatics and data management are crucial in helping to advance biomedical research. While many African countries are emerging in those specific fields, Cameroon and Central African countries in general, are still lagging behind. Based on this observation, in 2019, we created Bioinformatics and Biostatistics Hub (B2Hub) at the Biotechnology Center of the University of Yaounde I. Our aim through this platform is to promote bioinformatics and biostatistics among graduate students and young researchers from Central Africa.

Biopython 1.78 has been released and is available from our website and PyPI.

The main change is that Bio.Alphabet is no longer used. In some cases you will now have to specify expected letters, molecule type (DNA, RNA, protein), or gap character explicitly. Please consult the updated Tutorial and API documentation for guidance. This simplification has sped up many Seq object methods. See https://biopython.org/wiki/Alphabet for more information.

Bio.SeqIO.parse() is faster with “fastq” format due to small improvements in the Bio.SeqIO.QualityIO module.

Online. By at least a factor of two.

Our recent article entitled Lessons learnt from organizing a virtual conference discusses some of our technology choices and how we leveraged them to put on a successful online meeting. That article touches briefly on some of the challenges we faced, but it doesn’t fully convey how much work it was–both in advance and during the event.

Before we go any further, who are you? This post was written by Nomi Harris, the long-time (co-)chair of BOSC, and the co-chair (along with Dave Clements) of BCC2020 (the Bioinformatics Community Conference, a collaboration between the Bioinformatics Open Source Conference (BOSC) and the Galaxy Community Conference (GCC)). The perspective expressed in this post is mine alone, and does not necessarily reflect the views of others on the BCC2020 organizing committee. Also, although BCC2020 was an equal partnership between BOSC and GCC and the planning was done jointly (except for abstract reviews), my perspective is naturally BOSC-centric.

The Open Bioinformatics Foundation (OBF) Event Fellowship program aims to promote diverse participation at events promoting open source bioinformatics software development and open science practices in the biological research community. Pengfei Fan, a researcher from Queen Mary University of London, was supported to participate in CLEO 2020 by this fellowship granted to him in the application round-1 of 2020. Find more information here.

During the last two decades, we are witnessing a fascinating growth of computational imaging (CI) methods, e.g. tomography, compressive sensing and 3D/super-resolved/lensless microscopy, and artificial intelligence (AI) algorithms, mainly machine learning and deep learning, both from the theoretical (mathematical) and practical (experimental) point of view. New computational capabilities in terms of, e.g., big data, large scale optimisation, neural networks and highly parallel computing, are facilitating further improvements in numerically enhanced imaging surpassing the limitations imposed by ‘classical’ all-optical information processing systems. It is joyful to observe how CI and AI merge to innovatively address challenging tasks fuelled by wide-spreading applications in 3D imaging, biomedicine, microscopy and general physics of light propagation in scattering media, to name just a few. When designing a computational imaging technique, one needs to originally link the applicable data acquisition scheme with the capable image reconstruction algorithm, often aided by learning-based frameworks employed not only for image classification and interpretation but also for image formation and final outcome restoration. As the AI stimulatory development continues to flourish, open-source tools and software, especially deep learning framework and platform, have become a key ingredient of modern science. Hundreds of software packages, libraries, and applications have become essential tools.

We are glad to announce that the call for applications for the OBF Event Fellowship is now open. The deadline for this round is 1 October 2020. Applications should be submitted via this Google Form.

Renaming from “OBF Travel Fellowship” to “OBF Event Fellowship”

One of the goals of the OBF fellowship is to increase the participation of members from traditionally underrepresented groups at events or communities that promote Open Source software development and/or open science practices in the biological sciences. Since so many scientific meetings have been or are now run online, and we wish to explicitly support remote participation for this year, we are renaming ‘OBF Travel Fellowship’ to ‘OBF Event Fellowship’.

The Open Bioinformatics Foundation (OBF) Event Fellowship program aims to promote diverse participation at events promoting open source bioinformatics software development and open science practices in the biological research community. Gigi Kenneth, a biochemistry undergrad and a bioinformatics enthusiast from Nigeria, was supported to participate in Bioinformatics Community Conference 2020 by this fellowship granted to her in the application round-1 of 2020. Find more information here.

I’m a biochemistry undergraduate, in my final year from the University of Port Harcourt, Nigeria. I started learning about artificial intelligence and machine learning last year (2019), which I found really interesting and was really amazed by its applications in various fields. I found myself wondering about how these related to my graduate program, so I did some digging and was awed by the incredible work being done in this field.

The Open Bioinformatics Foundation (OBF) Event Fellowship program aims to promote diverse participation at events promoting open source bioinformatics software development and open science practices in the biological research community. Edidiong Etuk (Eddie), an open-source lover and a software engineer from Nigeria, was supported to take part in Bioinformatics Open Source Conference 2020 by this fellowship granted to him in the application round-1 of 2020. Find more information here.

TL;DR This post is about my experience at Bioinformatics Community Conference 2020.

BCC2020 (the collaborative BOSC + GCC meeting) was held online, with over 800 people registered for some part of the meeting. We used Remo.co as the technology platform, along with Discord for chat. Read about why we chose those, how it worked out, and our tips for others who are organizing virtual conferences here.

“Table view” in Remo during BCC2020

After much discussion, the BCC2020 organizing committee has decided to hold the meeting on Remo.co, which is similar to Zoom but offers a more conference-like experience, with “floors” and “tables” where you can mingle with other attendees. It has great small group and presentation support, including for posters and demos. It’s also more fun than most online conference platforms.

Because Remo is not familiar to most BCC participants, we are holding two open houses, one in each hemisphere, the day before BCC training starts. These walk-throughs will introduce participants to Remo’s features and demonstrate how to navigate between sessions, poster/demos, BoFs, training and everything else.

Biopython 1.77 has been released and is available from our website and PyPI.

This is the first release since we dropped support for Python 2.7 and 3.5. Focusing on Python 3.6 or later will let us take advantage of new functionality and syntax, and simplify our code base and testing.

This release of Biopython supports Python 3.6, 3.7 and 3.8 It has also been tested on PyPy3.6.1 v7.1.1.

pairwise2 now allows the input of parameters with keywords and returns the alignments as a list of namedtuples.