Mark A. Pauley

The CourseSource Bioinformatics Learning Framework

To The Editor: According to the Oxford English Dictionary (OED), bioinformatics is defined as “the branch of science concerned with information and information flow in biological systems, esp. the use of computational methods in genetics and genomics” (OED, 2015 ). Because the use of bioinformatics tools and approaches is becoming increasingly important for life scientists of all disciplines at all levels, it would be particularly advantageous for life sciences undergraduates to have some training in this field. As of yet, there is little agreement on a set of bioinformatics learning goals appropriate for undergraduate biology students. In an effort to move toward consensus in this area, we have developed a learning framework for a bioinformatics course that is part of the CourseSource initiative (Supplemental Material Table 1). CourseSource builds on the goals of Vision and Change in Undergraduate Education: A Call to Action (American Association for the Advancement of Science, 2011 ) by serving as a repository for tested teaching resources in a variety of different biological disciplines (Wright et al., 2013 ). CourseSource organizes teaching materials into courses that are part of the standard biology curriculum (http://coursesource.org). Each course is informed by a framework that has been vetted by an appropriate disciplinary society (e.g., the CourseSource framework for a genetics course was developed by representatives from the Education Committee of the Genetics Society of America). Core competencies for bioinformatics have been defined by the Curriculum Task Force of the Education Committee of the International Society for Computational Biology (Welch et al., 2014 ). The task force related the competencies to three different types of individuals requiring bioinformatics training: 1) bioinformatics engineers, who create novel computational methods needed by bioinformatics users and scientists; 2) bioinformatics scientists, who employ computational methods to advance the scientific understanding of living systems; and 3) bioinformatics users, who access data resources and bioinformatics tools to perform duties in specific application domains (e.g., medicine, law, agriculture, food science, education, etc.). As the starting place for the framework we used the bioinformatics user and bioinformatics scientist personas in particular (see table 2 in Welch et al., 2014 ) as well as our collective experience of integrating bioinformatics into our teaching. Three of us (M.A.P., A.G.R., and L.W.) worked collaboratively on the framework over several months, with input from S.C.R.E. and R.W. We then asked for feedback on the framework from groups with an interest in bioinformatics education, including members of the Genomics Education Partnership (http://gep.wustl.edu), the Network for Integrating Bioinformatics into Life Science Education (NIBLSE; http://niblse.unomaha.edu), and the Genome Consortium for Active Teaching NextGen Sequencing (http://lycofs01.lycoming.edu/∼gcat-seek), and participants in the Howard Hughes Medical Institute–sponsored Bioinformatics Workshop for Student/Scientist Partnerships that took place in June 2012 (http://gep.wustl.edu/hhmi_bioinformatics_workshop/index.html). The feedback we received was used to revise the framework. We are currently working with the International Society for Computational Biology to vet the framework. In addition, we expect that NIBLSE will also play a role in its ongoing development. As with most of the frameworks for other courses, the bioinformatics framework is organized around major topics with associated learning goals (framed as questions). A set of sample learning objectives, not meant to be exhaustive, is associated with each learning goal. In devising the framework (Supplemental Material Table 1), we organized the information around biological topics and computational ideas needed to address them. The first topic involves the role of computation in the life sciences. Subsequent topics involve concepts associated with the central dogma, beginning with DNA as the repository of genetic information, then considering RNA and proteins as means to express the genetic information. We next considered metabolomics and systems biology, exploring cellular homeostasis, and then examined topics in ecology and evolution, including metagenomics, thus moving from the level of individual cells to environmental samples. The final topic describes computational skills. CourseSource learning frameworks, including this one for bioinformatics, are not meant to be proscriptive. That is, there is no implication that a course should necessarily contain all of the elements in the associated framework. Instead, a course based on the learning framework will make use of an agreed-upon set of learning goals, and can take advantage of the associated expertise and materials posted in that particular field on CourseSource. For example, several of us teach bioinformatics courses that do not include substantial time spent on computer science skills, yet adhere to the overall learning goals and learning objectives within the framework. Overall, we feel that the existing framework will be generally applicable and useful to those attempting to launch a bioinformatics course at their institution for the first time. We therefore encourage all faculty members who are currently teaching bioinformatics to help populate the CourseSource bioinformatics framework with useful teaching materials to maximize utility of the site. Bioinformatics is an excellent way to introduce students to authentic research and is thus an effective means to achieve the goals of Vision and Change. We envision that the bioinformatics learning framework will continue to evolve as the field of bioinformatics grows. We welcome feedback from the life sciences community and encourage members to consider submitting their lessons, whether in bioinformatics or in other disciplines, to CourseSource.

Identification and distribution of high-abundance proteins in the octopus spring microbial mat community

ABSTRACT A shotgun metaproteomics approach was employed to identify proteins in a hot spring microbial mat community. We identified 202 proteins encompassing 19 known functions from 12 known phyla. Importantly, we identified two key enzymes involved in the 3-hydroxypropionate CO2 fixation pathway in uncultivated Roseiflexus spp., which are known photoheterotrophs.

A method of precise mRNA/DNA homology-based gene structure prediction.

BackgroundAccurate and automatic gene finding and structural prediction is a common problem in bioinformatics, and applications need to be capable of handling non-canonical splice sites, micro-exons and partial gene structure predictions that span across several genomic clones.ResultsWe present a mRNA/DNA homology based gene structure prediction tool, GIGOgene. We use a new affine gap penalty splice-enhanced global alignment algorithm running in linear memory for a high quality annotation of splice sites. Our tool includes a novel algorithm to assemble partial gene structure predictions using interval graphs. GIGOgene exhibited a sensitivity of 99.08% and a specificity of 99.98% on the Genie learning set, and demonstrated a higher quality of gene structural prediction when compared to Sim4, est2genome, Spidey, Galahad and BLAT, including when genes contained micro-exons and non-canonical splice sites. GIGOgene showed an acceptable loss of prediction quality when confronted with a noisy Genie learning set simulating ESTs.ConclusionGIGOgene shows a higher quality of gene structure prediction for mRNA/DNA spliced alignment when compared to other available tools.

A new approach for gene annotation using unambiguous sequence joining

The problem addressed by this paper is accurate and automatic gene annotation following precise identification/annotation of exon and intron boundaries of biologically verified nucleotide sequences using the alignment of human genomic DNA to curated mRNA transcripts. We provide a detailed description of a new cDNA/DNA homology gene annotation algorithm that combines the results of BLASTN searches and spliced alignments. Compared to other programs currently in use, annotation quality is significantly increased through the unambiguous junction of genomic DNA sequences. We also address gene annotation with both noncanonic splice sites and short exons. The approach has been tested on the genie learning subset as well as full-scale human RefSeq, and has demonstrated performance as high as 97%.

Applying, Evaluating and Refining Bioinformatics Core Competencies (An Update from the Curriculum Task Force of ISCB's Education Committee).

The Curriculum Task Force (CTF) of ISCB’s Education Committee seeks to define curricular guidelines for those who educate or train bioinformatics professionals at all career stages. A recent report of the CTF [1] presented a draft set of bioinformatics core competencies, derived from the results of surveys of (1) core facility directors, (2) career opportunities, and (3) existing curricula. Since the publication of its 2014 report, the CTF has focused on the application of the guidelines in varied contexts to identify areas where refinement is needed. As a first step, the task force held an open meeting at the ISMB conference in July 2014. The ideas discussed at the meeting spawned four working groups (WGs), which focus on (i) defining core competencies for specific types and levels of bioinformatics training, (ii) mapping the curriculum guidelines and competencies to existing materials in order to identify the need for development of new materials, and (iii) identifying where revision of the guidelines may be valuable. The CTF is engaging the ISCB community through open WG meetings at ISCB’s official conferences. Thus far, the WGs have convened at the ISCB Great Lakes Bioinformatics Conference (Purdue University, May 2015) and at the ISMB/ECCB Conference (Dublin, Ireland, July 2015). Additionally, the CTF held a workshop at the Annual General Meeting of the Global Organization of Bioinformatics Learning, Education and Training (Cape Town, South Africa, November 2015). Specifically, the draft competencies have been employed in a wide range of activities and contexts (see Table 1 and [2–11]), including the development of new curricula, the analysis of existing curricula, and the creation of new roles involving bioinformatics. These activities have resulted in the identification of several areas where refinement would be useful: Table 1 Summary of the activities of the ISCB Curriculum Task Force. Identify different levels or phases of competency. It would be helpful to define different phases of competency development, or different levels of competency appropriate for distinct roles. Define competency profiles for disciplines that don’t fit into our current silos. Bioengineering provides an illustrative example of a discipline that requires core competency in bioinformatics but does not fit into our current categories. There are almost certainly others. It would be helpful if we could provide some guidance on how to produce ‘hybrid’ competency profiles, perhaps borrowing some competencies from the TF’s core set and others from different disciplines. The LifeTrain initiative (www.lifetrain.eu) [2, 3] is collecting competency profiles for a range of disciplines of relevance to the biomedical sciences and may provide a useful resource kit for this. Broaden the scope of the competency profiles in response to cutting-edge and emerging research. Current areas requiring improvement include incorporating competencies that capture a fundamental understanding of the biological principles central to analyzing biomolecular data, and broadening the user WG to include applications beyond medicine. Provide guidance on the evidence required to assess whether someone has acquired each competency. For undergraduate, Master’s and PhD programs, learning outcomes for each competency, perhaps with examples of appropriate means of assessment, would be valuable. For established professionals who need to assimilate competencies into their working lives, a different approach may be required (such as keeping a portfolio to capture evidence of competency); the CTF should seek guidance from relevant professional bodies, especially in regulated professions such as healthcare. Provide indicative course content or examples of programs that map to the competency requirements. We do not wish to prescribe what course providers should teach or how they should teach it; however, if a course provider is designing a course to meet a specific competency requirement, it may be helpful to find examples of other programs that do this successfully. One way of achieving this is by mapping existing training content to the TF’s competencies. Another way might be to provide an indication, perhaps based on several courses, of the course content that would meet the competency requirements. This would give course providers the freedom to build their own course syllabi without having to reinvent the wheel. Initiatives to collect examples of Creative Commons (or otherwise reusable) course materials will provide an extremely valuable bank of training materials that could be mapped to the core competencies.

The development and application of bioinformatics core competencies to improve bioinformatics training and education

Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans.

Barriers to Integration of Bioinformatics into Undergraduate Life Sciences Education

Bioinformatics, a discipline that combines aspects of biology, statistics, and computer science, is increasingly important for biological research. However, bioinformatics instruction is rarely integrated into life sciences curricula at the undergraduate level. To understand why, the Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE, “nibbles”) recently undertook an extensive survey of life sciences faculty in the United States. The survey responses to open-ended questions about barriers to integration were subjected to keyword analysis. The barrier most frequently reported by the ~1,260 respondents was lack of faculty training. Faculty at associate’s-granting institutions report the least training in bioinformatics and the least integration of bioinformatics into their teaching. Faculty from underrepresented minority groups (URMs) in STEM reported training barriers at a higher rate than others, although the number of URM respondents was small. Interestingly, the cohort of faculty with the most recently awarded PhD degrees reported the most training but were teaching bioinformatics at a lower rate than faculty who earned their degrees in previous decades. Other barriers reported included lack of student interest in bioinformatics; lack of student preparation in mathematics, statistics, and computer science; already overly full curricula; and limited access to resources, including hardware, software, and vetted teaching materials. The results of the survey, the largest to date on bioinformatics education, will guide efforts to further integrate bioinformatics instruction into undergraduate life sciences education.

Bioinformatics core competencies for undergraduate life sciences education

Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent’s degree of training, time since degree earned, and/or the Carnegie Classification of the respondent’s institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula.

Acquisition and review of diagnostic images for use in medical research and medical testing examinations via the Internet

With the continued centralization of medical care into large, regional centers, there is a growing need for a flexible, inexpensive, and secure system to rapidly provide referring physicians in the field with the results of the sophisticated medical tests performed at these facilities. Furthermore, the medical community has long recognized the need for a system with similar characteristics to maintain and upgrade patient case sets for oral and written student examinations. With the move toward filmless radiographic instrumentation, the widespread and growing use of digital methods and the Internet, both of these processes can now be realized. This article describes the conceptual development and testing of a protocol that allow users to transmit, modify, remotely store and display the images and textual information of medical cases via the Internet. We also discuss some of the legal issues we encountered regarding the transmission of medical information; these issues have had a direct impact on the implementation of the results of this project.