bioinformatics as engineering or science? a tale of two degrees - bruno gaeta
DESCRIPTION
The need for just-in-time bioinformatics training for biologists is well-established. However the jury is still out when it comes to formal education in bioinformatics. Bioinformaticians are called to apply computational methods to life science data with the view of contributing to biological discoveries – a scientific task, but they are also often required to design and implement new methods and infrastructure for life science computing – a task that draws on engineering skills and mindset. Putting the two together into one degree is difficult especially at the undergraduate level given the breadth of foundational knowledge required. UNSW has for the last 13 years offered a degree in Bioinformatics engineering with a strong engineering core. This degree is now being complemented by a Bachelor of Science in bioinformatics that aims to train biologists with a strong computational focus. The two degrees share common courses but each has a distinct emphasis and target audience. Presented at InCoB 2014 special session on Bioinformatics Education and Training: http://incob2014.orgTRANSCRIPT
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Bioinformatics: science or engineering?
A tale of two degrees
Bruno Gaëta
Who are bioinformaticians?
Computational biologists
Software developers
Engineers
Biologists who use computers
Biology problems
Working software
Algorithms
Infrastructure
Discovery in biology
Table 2. Core competencies for each bioinformatics training category.
Welch L, Lewitter F, Schwartz R, Brooksbank C, et al. (2014) Bioinformatics Curriculum Guidelines: Toward a Definition of Core Competencies. PLoS Comput Biol 10(3): e1003496. doi:10.1371/journal.pcbi.1003496http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003496
School of Computer Science and Engineering
Bioinformatics engineers create the novel computational methods needed by bioinformatics users and scientists [25], [26]. Thus, a bioinformatics engineer must have strengths in computational and statistical sciences and must have general competency in biomedical sciences. Bioinformatics engineers design the infrastructure and systems for bioinformatics analysis, integrating software, databases, and hardware. This can involve the choice or design of hardware and software for the storage and management of diverse and distributed data, selection or development of tools and algorithms for integration and analysis of these data, and design of suitable user interfaces. The critical and complex nature of bioinformatics software and the growing volume of associated data require the development of reliable and maintainable systems in an environment where requirements can be complex, vague, and volatile, and budgets and schedules are often tight. In addition to strong scientific foundations and technical skills the bioinformatics engineer needs to bring to bear engineering competencies such as systems design and project management to ensure the quality, viability, and sustainability of the software systems developed.
Welch L, Lewitter F, Schwartz R, Brooksbank C, et al. (2014) Bioinformatics Curriculum Guidelines: Toward a Definition of Core Competencies. PLoS Comput Biol 10(3): e1003496. doi:10.1371/journal.pcbi.1003496http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003496
School of Computer Science and Engineering
UNSW Bachelor of Engineering (Bioinformatics
Engineering)• Started in 2001 - oldest surviving undergraduate bioinformatics degree in Australia
• Accredited as an engineering degree by Engineers Australia
• 4 year program with included Honours• Recent accreditation/revision increased
engineering component at the expense of biological content
School of Computer Science and Engineering
Bachelor of Science (Bioinformatics)
• New major, starting in 2015• Aimed at training bioinformatics
scientists• 3 years program – 4th year Honours
is optional and requires a WAM over 65
School of Computer Science and Engineering
Year 1
Bachelor of Engineering•BABS 1201 Molecules Cells Genes•COMP1917 Computing 1•COMP1927 Computing 2•MATH1131 Maths 1A•MATH1231 Maths 1B•CHEM1011 Chemistry 1A•PHYS1121 Physics 1A•ENGG1000 Engineering Design
Bachelor of Science•BABS 1201 Molecules Cells Genes•COMP1917 Computing 1•COMP1927 Computing 2•MATH1131 Maths 1A•MATH1231 Maths 1B•CHEM1011 Chemistry 1A•CHEM1021 Chemistry 1B•1 Science elective
School of Computer Science and Engineering
Year 2
Bachelor of Engineering
•MATH2801 Theory of Statistics
•BIOC2201 Molecular Biology
•BINF2010 Intro to Bioinformatics
•COMP2041 Software Construction
•Biochemistry or Genetics or Cell Biology or Microbiology
•COMP2911 Engineering Design in Computing
•SENG1031 Software Engineering Workshop
•MATH1081 Discrete Maths
Bachelor of Science•MATH2801 Theory of Statistics•BIOC2201 Molecular Biology•BINF2010 Intro to Bioinformatics•COMP2041 Software Construction•BIOC2201 Biochemistry•3 Science electives
School of Computer Science and Engineering
Year 3
Bachelor of Engineering•BINF3010 Bioinformatics Methods•BINF3020 Computational Bioinformatics•BABS3121 Molecular Biology of Nucleic Acids•COMP3121 Algorithms•COMP3311 Databases•BINF3111 Bioinformatics Design Project A•2 x Electives
Bachelor of Science•BINF3010 Bioinformatics Methods•BINF3020 Computational Bioinformatics•BABS3121 Molecular Biology of Nucleic Acids•2 x General Education•3 x Electives
School of Computer Science and Engineering
Year 4: Optional for Science Students
Bachelor of Engineering•Thesis Project•BINF4111 Bioinformatics Design Project B•COMP4920 Management and Ethics•2 x General Education•2 x Bioinformatics Electives
Bachelor of Science •Thesis Project•Optional: advanced science and computing electives
School of Computer Science and Engineering
Bioinformatics courses
• BINF2010 Introduction to Bioinformatics• BINF3010 Bioinformatics Methods and
Applications• BINF3020 Computational Bioinformatics • BINF3111 Bioinformatics Design Project A• BINF4111 Bioinformatics Design Project B
School of Computer Science and Engineering
BINF2010 Introduction to Bioinformatics
The course surveys the major areas of bioinformatics, exploring the history of bioinformatics in relation to advances in computing hardware and software; the biological problems currently being addressed using bioinformatics; and future applications of bioinformatics. Major topics include genomics; genome sequencing projects; proteomics; structural genomics; systems biology; phylogeny; medical informatics; and commercial applications of bioinformatics. The general nature of the data, computational problems and the approaches employed will be discussed in each case. Bioinformatics will be discussed both as a scientific discipline and as an engineering discipline. The course will also explore the role of bioinformatics in the biotechnology and pharmaceutical industries and ethical issues associated with biological data. Lectures are supplemented by practical exposure to public and commercial bioinformatics web sites and to commonly used bioinformatics software.
School of Computer Science and Engineering
BINF3010 Bioinformatics Methods and Applications
Bioinformatics (the use of computing methods for the management and analysis of molecular biology data) has become an integral component of biomolecular sciences, especially genomics and proteomics. This course focuses on the principles and practical use of bioinformatics methods and resources for the analysis of DNA and protein sequences and structures, as well as results from microarray and proteomics, with emphasis on their evolutionary underpinnings and statistical foundations.This course does not require programming, however it does involve the use of Linux.
School of Computer Science and Engineering
BINF3020 Computational Bioinformatics
Algorithms and representations in DNA and protein sequence analysis: string matching and alignment, tree building methods, hidden Markov models and other statistical representations. Computational representations in systems biology including Boolean and Bayesian networks. Optimisation and machine learning approaches used in bioinformatics.
School of Computer Science and Engineering
BINF3111 Bioinformatics Engineering Design Project
ABioinformatics engineering involves the design of software systems for analysing large quantities of complex and diverse data. This practical course revolves around a guided team project for the design and implementation of a complex system bringing together a variety of tools and methods for analysing genomic data. Methodologies for requirement gathering, system design, project management and documentation will be applied. The project work will be complemented by lectures on formal and practical aspects of engineering design and management, bioinformatics development environments and workflow management systems.
School of Computer Science and Engineering
BINF4111 Bioinformatics Engineering Design Project
BBuilding on the project work in BINF3111, this course examines various issues in the design and implementation of software systems for the analysis of large complex biological datasets including algorithm choice and design, data management, user interface design, workflow auditing and reproducibility, software licensing, testing and verification, ethical considerations and sustainability, as well as software project management in environments of complex, vague and volatile requirements and tight budgets and schedules.