Bioinformatics Modules Research Articles

Bioinformatics in Russia: history and present-day landscape.

Bioinformatics has become an interdisciplinary subject due to its universal role in molecular biology research. The current status of Russia's bioinformatics research in Russia is not known. Here, we review the history of bioinformatics in Russia, present the current landscape, and highlight future directions and challenges. Bioinformatics research in Russia is driven by four major industries: information technology, pharmaceuticals, biotechnology, and agriculture. Over the past three decades, despite a delayed start, the field has gained momentum, especially in protein and nucleic acid research. Dedicated and shared centers for genomics, proteomics, and bioinformatics are active in different regions of Russia. Present-day bioinformatics in Russia is characterized by research issues related to genetics, metagenomics, OMICs, medical informatics, computational biology, environmental informatics, and structural bioinformatics. Notable developments are in the fields of software (tools, algorithms, and pipelines), use of high computation power (e.g. by the Siberian Supercomputer Center), and large-scale sequencing projects (the sequencing of 100 000 human genomes). Government funding is increasing, policies are being changed, and a National Genomic Information Database is being established. An increased focus on eukaryotic genome sequencing, the development of a common place for developers and researchers to share tools and data, and the use of biological modeling, machine learning, and biostatistics are key areas for future focus. Universities and research institutes have started to implement bioinformatics modules. A critical mass of bioinformaticians is essential to catch up with the global pace in the discipline.

Conceptualizing bioinformatics education in STEM literacy development for pre-service biology teachers

This study aimed to create a basic plan for adding bioinformatics education into STEM (Science, Technology, Engineering, and Mathematics) learning, particularly for future biology teachers. By reviewing studies from 2019 to 2023 in the ERIC Database with the key terms "Bioinformatics Education" and "STEM Literacy," the research highlighted important areas in this subject. It organized the findings into four main themes related to bioinformatics education: levels of education, challenges faced, teaching methods, and methods for research or evaluation. Additionally, it identified three themes in STEM literacy: educational levels, challenges, and definitions or ways to measure it. The review pointed out a critical need for teaching materials, tools, and strategies in bioinformatics for future biology teachers at the college level. It also found a lack of research on STEM literacy at this level, with just three articles addressing it. These articles examined STEM literacy through skills such as general knowledge, career awareness, and communication skills. The suggested basic plan promotes combining bioinformatics education with real-world biological issues, career preparation, and addressing educational shortcomings. It recommends a bioinformatics module with specific curriculum content, tools, and teaching methods to improve STEM literacy, including knowledge, attitudes, and skills in STEM. This plan could guide future research in classrooms to improve STEM literacy among future biology teachers through bioinformatics education.

Saccharomyces cerevisiae YIL164C/NIT1 is a Putative Nitrilase

While the yeast Saccharomyces cerevisiae is a well‐studied organism with its genome fully sequenced two decades ago, there remain several hundred uncharacterized open reading frames, ORFans, with no significant sequence homology to other genes. As ORFan roles cannot be determined solely through sequence homology, their functions remain a mystery until both in vitroand in vivobiochemical and cell biology experiments are performed. In collaboration with the Yeast ORFan Gene Project, we used bioinformatics modules to initially characterize one such ORFan, YIL165C.We found that together with the gene immediately preceding it, YIL164C (NIT1), the two genes have significant homology to the nitrilase superfamily of proteins but have low sequence homology to the other two S. cerevisiae nitrilases NIT2 and NIT3. Interestingly, the YIL164C protein alone contains both the conserved catalytic triad and a region that shares homology with prokaryotic nitrilases that specifically target aromatic, rather than aliphatic, nitrile substrates. We additionally experimentally verified that lab strains of S. cerevisiae, such as BY4741, SEY6210, and GA74, have a bonafide stop codon breaking up the two proteins in clones from both genomic DNA and mRNA, while the brewing yeast strain WLP001 (White Labs) and other related yeast strains have a single nucleotide polymorphism (SNP; A to G transition) allowing these two proteins to be expressed as a single, continuous polypeptide chain. To understand the function of both the full‐length YIL164C/YIL165C and the truncated YIL164C protein, we expressed and purified the proteins in bacteria and began initial studies to understand their substrate preference. We hope to identify distinctions in activity, or the lack thereof, between the longer and the truncated proteins. Understanding these enzymes in vitro will provide clues to their in vivo functions and the evolutionary relationships among genes in this superfamily.

The Effect of Bioinformatics Module on Molecular Genetics Concepts on Senior High School Students’ Computational Thinking Skills

This study aimed to investigate senior high school students’ computational thinking skills after implementing the Bioinformatics Module on molecular genetics concepts. The instructional approach used in the module is Computational Inquiry-based Teaching (CIbT). This study used a quasi-experiment method with a pretest-posttest control group design. The subjects in this study consist of 24 students in the control group and 38 students in the experimental group from a senior high school in Indonesia. The instrument used in this study is six items of computational thinking test. This module had four themes; Genetics Disease, Cancer, Forensic Science, and Evolution, conducted in 8 sessions. Each session lasted 90 minutes. The Bioinformatics Module consists of programming and databases, including unplugged computational activities and unplugged activities including coding using Python, searching in Uniprot, and using BLAST in NCBI. The CIbT has five steps: orientation, conceptualization, investigation, conclusion, and discussion. The Mann-Whitney test results showed that the p-value from N-Gain data is < 0.01. So, Bioinformatics Module on molecular genetics concepts using CIbT can improve computational thinking skills of senior high school students. For further implementation, biology teachers must prepare to use the Bioinformatics Module, including biology teachers’ understanding of molecular genetics and bioinformatics practices to enrich the learning experience in the Bioinformatics Module.

The microRNA analysis portal is a next-generation tool for exploring and analyzing miRNA-focused data in the literature

MicroRNAs constitute a class of noncoding small RNAs involved in the posttranscriptional regulation of many biological pathways. In recent years, microRNAs have also been associated with regulation across kingdoms, demonstrating that exogenous miRNAs can function in mammals in a fashion similar to mammalian miRNAs. The growing interest in microRNAs and the increasing amount of literature and molecular and biomedical data available make it difficult to identify records of interest and keep up to date with novel findings. For these reasons, we developed the microRNA Analysis Portal (MAP). MAP selects relevant miRNA-focused articles from PubMed, links biomedical and molecular data and applies bioinformatics modules. At the time of this writing, MAP represents the richest, most complete and integrated database focused on microRNAs. MAP also integrates an updated version of MirCompare (2.0), a computational platform used for selecting plant microRNAs on the basis of their ability to regulate mammalian genes. Both MAP and MirCompare functionalities were used to predict that microRNAs from Moringa oleifera have putative roles across kingdoms by regulating human genes coding for proteins of the immune system. Starting from a selection of 94 human microRNAs, MirCompare selected 6 Moringa oleifera functional homologs. The subsequent prediction of human targets and areas of functional enrichment highlighted the central involvement of these genes in regulating immune system processes, particularly the host-virus interaction processes in hepatitis B, cytomegalovirus, papillomavirus and coronavirus. This case of use showed how MAP can help to perform complex queries without any computational background. MAP is available at http://stablab.uniroma2.it/MAP.

Abstract 2516: A bioinformatics framework for high-sensitivity detection and monitoring of oncogenic gene fusions in plasma cfDNA

Abstract Gene fusions represent key oncogenic driver alterations in many solid tumors that can be targeted therapeutically. Beyond FDA-approved drugs targeting ALK and ROS1 fusions in lung cancer, investigational agents targeting gene fusions involving RET, NTRK1/2/3, and FGFR2/3 have elicited significant and durable responses in a wide range of cancer types. Cell-free DNA (cfDNA) profiling provides a transformative opportunity to non-invasively and longitudinally monitor responses to these investigational therapies and identify acquired mutations that confer drug resistance. We have developed a pan-cancer, high-sensitivity NGS cancer assay (MSK-ACCESS, presented previously) to detect and monitor somatic mutations in plasma cfDNA. Here, we present an improved bioinformatics pipeline that detects gene fusions and achieves greater sensitivity and accuracy for detecting point mutations and indels. MSK-ACCESS uses ultra-high depth sequencing (~20,000x) coupled with duplex unique molecular indexing (UMI) and dual sample barcodes to achieve high sensitivity through background error suppression. The panel was designed to capture key exons and domains of 129 cancer genes as well as introns harboring recurrent breakpoints in 10 commonly rearranged genes. We have now developed a bioinformatics module for sensitive detection of structural variation from cfDNA, leveraging the high-depth sequencing data and intronic coverage. We have also added a statistical polishing method that assigns confidence to detected somatic mutations by building frequency distributions for those mutations from a large set of normal samples that has been processed with the same laboratory protocol and bioinformatics pipeline as the patient samples. In parallel, we have further improved the wet lab protocols to address challenges of capturing sufficient numbers of cfDNA molecules and removing noise, both required for detection of somatic mutations with high sensitivity and specificity. Using this method, we have successfully detected druggable fusions in plasma cfDNA from patients spanning a diverse set of cancer types. Through longitudinal cfDNA collection efforts embedded within early-phase clinical trials, we demonstrate that the levels of oncogenic driver fusions in cfDNA may scale with the burden of disease. Moreover, the ability to simultaneously call high-confidence mutations at low allele fractions has revealed novel acquired mutations indicative of polyclonal resistance to investigational targeted therapies. Citation Format: Juber Patel, Maysun Hasan, Fanli Meng, Xiaohong Jing, Grittney Tam, Ian Johnson, Youyun Zheng, Chaitanya Bandlamudi, Caitlin Stewart, Helen Won, Oliver Hampton, Alison Schram, Ezra Rosen, Alexander Drilon, Anna Varghese, David Hyman, Dana Tsui, Brian Houck-Loomis, Michael Berger. A bioinformatics framework for high-sensitivity detection and monitoring of oncogenic gene fusions in plasma cfDNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2516.

Fostering bioinformatics education through skill development of professors: Big Genomic Data Skills Training for Professors.

Bioinformatics has become an indispensable part of life science over the past 2 decades. However, bioinformatics education is not well integrated at the undergraduate level, especially in liberal arts colleges and regional universities in the United States. One significant obstacle pointed out by the Network for Integrating Bioinformatics into Life Sciences Education is the lack of faculty in the bioinformatics area. Most current life science professors did not acquire bioinformatics analysis skills during their own training. Consequently, a great number of undergraduate and graduate students do not get the chance to learn bioinformatics or computational biology skills within a structured curriculum during their education. To address this gap, we developed a module-based, week-long short course to train small college and regional university professors with essential bioinformatics skills. The bioinformatics modules were built to be adapted by the professor-trainees afterward and used in their own classes. All the course materials can be accessed at https://github.com/TheJacksonLaboratory/JAXBD2K-ShortCourse.

Blending Gagne's Instructional Model with Peyton's Approach to Design an Introductory Bioinformatics Lesson Plan for Medical Students: Proof-of-Concept Study.

BackgroundWith the rapid integration of genetics into medicine, it has become evident that practicing physicians as well as medical students and clinical researchers need to be updated on the fundamentals of bioinformatics. To achieve this, the following gaps need to be addressed: a lack of defined learning objectives for “Bioinformatics for Medical Practitioner” courses, an absence of a structured lesson plan to disseminate the learning objectives, and no defined step-by-step strategy to teach the essentials of bioinformatics in the medical curriculum.ObjectiveThe objective of this study was to address these gaps to design a streamlined pedagogical strategy for teaching basics of bioinformatics in the undergraduate medical curriculum.MethodsThe established instructional design strategies employed in medical education—Gagne’s 9 events of instruction—were followed with further contributions from Peyton’s four-step approach to design a structured lesson plan in bioinformatics.ResultsFirst, we defined the specifics of bioinformatics that a medical student or health care professional should be introduced to use this knowledge in a clinical context. Second, we designed a structured lesson plan using a blended approach from both Gagne’s and Peyton’s instructional models. Lastly, we delineated a step-by-step strategy employing free Web-based bioinformatics module, combining it with a clinical scenario of familial hypercholesterolemia to disseminate the defined specifics of bioinformatics. Implementation of Schon’s reflective practice model indicated that the activity was stimulating for the students with favorable outcomes regarding their basic training in bioinformatics.ConclusionsTo the best of our knowledge, the present lesson plan is the first that outlines an effective dissemination strategy for integrating introductory bioinformatics into a medical curriculum. Further, the lesson plan blueprint can be used to develop similar skills in workshops, continuing professional development, or continuing medical education events to introduce bioinformatics to practicing physicians.

Design and implementation of structural bioinformatics projects for biological sciences undergraduate students.

Contemporary biology is currently undergoing a revolution, driven by the availability of high-throughput technologies and a wide variety of bioinformatics tools. However, bioinformatics education and practice is still in its infancy in most of the African continent. Consequently, concerted efforts have been made in recent years to incorporate bioinformatics modules into biological sciences curriculum of African Universities. Despite this, one aspect of bioinformatics that is yet to be incorporated is structural bioinformatics. In this article, we report on a structural bioinformatics project carried out by final year project students in a Nigerian university. The target protein was the thermoacidophilic Sulfolobus islandicus rod-shaped virus 1 (SIRV1) Rep protein, which was further characterized using various free, user-friendly and online sequence-based and structure-based bioinformatics tools. This exercise gave students the opportunity to generate new data, interpret the data, and acquire collaborative research skills. In this report, emphasis is placed on analysis of the data generated to further encourage analytical skills. By sharing this experience, it is anticipated that other similar institutions would adopt parallel strategies to expose undergraduate students to structural biology, and increase awareness of freely available bioinformatics tools for tackling pertinent biological questions. © 2018 International Union of Biochemistry and Molecular Biology, 46(5):547-554, 2018.

‘Students-as-partners’ scheme enhances postgraduate students’ employability skills while addressing gaps in bioinformatics education

Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student–staff partnership and peer-learning. It was centred on the experiences of peer-facilitators, students who had previously taken a postgraduate bioinformatics module, and had applied knowledge and skills gained from it to their own research. It aimed to demonstrate to peer-receivers, current students, how bioinformatics could be used in their own research while developing peer-facilitators’ teaching and mentoring skills. This student-centred approach was well received by the peer-receivers, who claimed to have gained improved understanding of bioinformatics and its relevance to research. Equally, peer-facilitators also developed a better understanding of the subject and appreciated that the activity was a rare and invaluable opportunity to develop their teaching and mentoring skills, enhancing their employability.

Evaluating the effectiveness of a practical inquiry-based learning bioinformatics module on undergraduate student engagement and applied skills.

A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion, qualitative student-based module evaluation and the novelty, scientific validity and quality of written student reports. Bioinformatics is often the starting point for laboratory-based research projects, therefore high importance was placed on allowing students to individually develop and apply processes and methods of scientific research. Students led a bioinformatic inquiry-based project (within a framework of inquiry), discovering, justifying and exploring individually discovered research targets. Detailed assessable reports were produced, displaying data generated and the resources used. Mimicking research settings, undergraduates were divided into small collaborative groups, with distinctive central themes. The module was evaluated by assessing the quality and originality of the students' targets through reports, reflecting students' use and understanding of concepts and tools required to generate their data. Furthermore, evaluation of the bioinformatic module was assessed semi-quantitatively using pre- and post-module quizzes (a non-assessable activity, not contributing to their grade), which incorporated process- and content-specific questions (indicative of their use of the online tools). Qualitative assessment of the teaching intervention was performed using post-module surveys, exploring student satisfaction and other module specific elements. Overall, a positive experience was found, as was a post module increase in correct process-specific answers. In conclusion, an inquiry-based peer-assisted learning module increased students' engagement, practical bioinformatic skills and process-specific knowledge. © 2016 by The International Union of Biochemistry and Molecular Biology, 44:304-313 2016.

A Bioinformatics Module for Use in an Introductory Biology Laboratory

Since biomedical science has become increasingly data-intensive, acquisition of computational and quantitative skills by science students has become more important. For non-science students, an introduction to biomedical databases and their applications promotes the development of a scientifically literate population. Because typical college introductory biology laboratories do not include experiences of this type, we present a bioinformatics module that can easily be included in a 90-minute session of a biology course for both majors and non-majors. Students completing this computational, inquiry-based module observed the value of computer-assisted analysis. The module gave students an understanding of how to read files in a biological database (GenBank) and how to use a software tool (BLAST) to mine the database.

Bioinformatics and the Undergraduate Curriculum

Recent advances involving high-throughput techniques for data generation and analysis have made familiarity with basic bioinformatics concepts and programs a necessity in the biological sciences. Undergraduate students increasingly need training in methods related to finding and retrieving information stored in vast databases. The rapid rise of bioinformatics as a new discipline has challenged many colleges and universities to keep current with their curricula, often in the face of static or dwindling resources. On the plus side, many bioinformatics modules and related databases and software programs are free and accessible online, and interdisciplinary partnerships between existing faculty members and their support staff have proved advantageous in such efforts. We present examples of strategies and methods that have been successfully used to incorporate bioinformatics content into undergraduate curricula.

Vertical and horizontal integration of bioinformatics education

Bioinformatics education for undergraduates has been approached primarily in two ways: introduction of new courses with largely bioinformatics focus or introduction of bioinformatics experiences into existing courses. For small colleges such as Kalamazoo, creation of new courses within an already resource-stretched setting has not been an option. Furthermore, we believe that a true interdisciplinary science experience would be best served by introduction of bioinformatics modules within existing courses in biology and chemistry and other complementary departments. To that end, with support from the Howard Hughes Medical Institute, we have developed over a dozen independent bioinformatics modules for our students that are incorporated into courses ranging from general chemistry and biology, advanced specialty courses, and classes in complementary disciplines such as computer science, mathematics, and physics. These activities have largely promoted active learning in our classrooms and have enhanced student understanding of course materials. Herein, we describe our program, the activities we have developed, and assessment of our endeavors in this area.

Bioinformatics for Undergraduate Biochemistry Courses at Kalamazoo College

In 2004 Kalamazoo College received a gift from the Howard Hughes Medical Institute to support development of bioinformatics education in the Biochemistry and Molecular Biology Concentration – a joint program between the Chemistry and Biology Departments. Bioinformatics modules were introduced over a period of four years into 10 courses in Biology, Chemistry, and Computer Science. Bioinformatics modules introduced in Biochemistry and Advanced Biochemistry are presented here. Modules described include use of the following tools, databases, and search engines: BLAST, KEGG, OMIM, BRENDA, Protein Data Bank, ExPASy, Protein Explorer, Swiss Deep View, and VAST. In addition, a new module using tools for investigating intrinsic protein disorder is described. Student assessment of the experiences is given. (This work was supported by an HHMI grant to Kalamazoo College).

Cancer onset and progression: A genome-wide, nonlinear dynamical systems perspective on onconetworks

It is hypothesized that the many human cell types corresponding to multiple states is supported by an underlying nonlinear dynamical system (NDS) of transcriptional regulatory network (TRN) processes. This hypothesis is validated for epithelial cells whose TRN is found to support an extremely complex array of states that we term a “bifurcation nexus”, for which we introduce a quantitative measure of complexity. The TRN used is constructed and analyzed by integrating a database of TRN information, cDNA microarray data analyzers, bioinformatics modules, a transcription/translation/post-translation kinetic model, and NDS analysis software. Results of this genome-wide approach suggest that a cell can be induced to persist in one state or to transition between distinct states; apparently irreversible transitions can be reversed when the high dimensional space of extracellular and intracellular parameters is understood. As conditions change, certain cellular states (cell lines) are no longer supported, new ones emerge, and transitions (cell differentiation or death) occur. The accumulation of simulated point mutations (minor changes which individually are insignificant) lead to occasional dramatic transitions. The genome-wide scope of many of these transitions is shown to arise from the cross-linked TRN structure. These notions imply that studying individual oncogenes may not be sufficient to understand cancer; rather, “onconetworks” (subsets of strongly coupled genes supporting multiple cell states) should be considered. Our approach reveals several epithelial onconetworks, each involving oncogenes and anti-tumor and supporting genes.

SCORPION, a molecular database of scorpion toxins

Increasing interest in the studies of toxins and the requirements for better structural and functional annotations have created a need for improved data management in the field of toxins. The molecular database, SCORPION, contains more than 200 entries of fully referenced scorpion toxin data including primary sequences, three-dimensional structures, structural and functional annotations of scorpion toxins along with relevant literature references. SCORPION has a set of search tools that allow users to extract data and perform specific queries. These entries have been compiled from public databases and literature, cleaned of errors and enriched with additional structural and functional information. The grouping of scorpion toxins provides a basis for extending and clarifying the existing structural and functional classifications. The bioinformatics modules in SCORPION facilitate analyses aimed at classification of scorpion toxins and identification of sequence patterns associated with specific structural or functional properties of scorpion toxins. The SCORPION database is accessible via the Internet at sdmc.krdl.org.sg:8080/scorpion.