Claire O’Donovan, leader of the Protein Function Content team at EMBL-EBI, gives an introduction into biocuration and talks about what it is like to work as a biocurator and the skill sets you need.

This webinar was recorded on 2 March 2016 and is best viewed using Google Chrome and in full-screen mode.

These Online Educational Resources (OERs) cover a variety of topics related to data science and are intended for use in courses, programs, workshops, and related activities.

Modules relevant to biocuration:

• BDK05 Basic Research Data Standards (https://github.com/OHSUBD2K/BDK05-Basic-Research-Data-Standards). Standards for biomedical data, participating in communities that develop them, aiding reproducibility.
• BDK11 Identifiers (https://github.com/OHSUBD2K/BDK11-Identifiers). Introduction to identifiers (modeling, identifying and describing resources and objects.)
• BDK12 Data Annotation And Curation (https://github.com/OHSUBD2K/BDK12-Data-annotation-and-curation). Data preparation, developing standardized quality assurance processes and pipelines.
• BDK14 Ontologies 101 (https://github.com/OHSUBD2K/BDK14-Ontologies-101). Introduction to OWL2 and data reasoning.

Authors: OHSU BD2K team

Type of Material: Presentation slides, videos (in BDK12), exercises, and other resources.

License: CC-BY

“Evolution Academy” videos (https://www.queensu.ca/academia/forsdyke/videolectures.htm).

The latter are a course of 54 short (15 min) videos that follow the style of Salman Khan’s “Khan Academy,” and are addressed primarily to High School and beginning College students.

There are also several longer (1 h) conference presentations that bring together various themes.

These are backed by several webpages (accessible by way of https://www.queensu.ca/academia/forsdyke), and a textbook, now in its third edition (2016; for Introduction see Materials File).

Next generation sequencing (NGS) has become a commodity. With the commercialization of various affordable desktop sequencers, NGS will be of reach by more traditional wet-lab biologists . As seen in recent years, genome-wide scale computational analysis is increasingly being used as a backbone to foster novel discovery in biomedical research. However, as the quantities of sequence data increase exponentially, the analysis bottle-neck is yet to be solved.

The current sources for NGS informatics are extremely fragmented. A novice could read review articles in various journals, follow discussion threads on forums such as Biostar^[1] or SEQanswers ^[2], or sign up for courses organized by various institutes. Finding a centralized synthesis is much more difficult. Books are available, but the development of the field is so fast that book chapters risk being obsoleted by the time they are even printed. Moreover, cost for a handful of authors to continually update their text would presumably take up a lot of their schedule.

Drawing from the obvious goodwill and community spirit displayed on discussion forums, and exploiting the collaborative tools made available by the Wikimedia foundation, we propose to initiate the editing of a collaborative WikiBook on NGS. Our plan is to collect a sufficient amount of text that people will be incentivized to contribute to it, essentially providing the same information as a forum but in a tidier form. Ultimately, our goal is to create a collective lab book that explains the key concepts and describes best practices in NGS.

1. Parnell LD, Lindenbaum P, Shameer K et al. BioStar: an online question & answer resource for the bioinformatics community, PLoS Comput Biol 2011;7:e1002216.
2. Li JW, Schmieder R, Ward RM et al. SEQanswers: an open access community for collaboratively decoding genomes, Bioinformatics 2012;28:1272-1273

Read about this initiative and the nine rules for NGS data analysis here: The NGS WikiBook: a dynamic collaborative online training effort with long-term sustainability