User:Calvin A. Mok
- Calvin A. Mok
- University of Washington, Department of Genome Sciences
- 3720 15th Ave NE, Room S343E
- Seattle, WA, USA.
- Email me through OpenWetWare
I work in the Waterston Lab at the University of Washington studying the model organism Caenorhabditis elegans. My main interest is in developing exciting methods that can be used in identifying and analysing genetic interactions in the nematode.
- 2012, PhD, University of Toronto, Institute of Medical Sciences.
- 2005, BMath with Bioinformatics option, University of Waterloo, Faculty of Mathematics
- Investigating gene function through the formation of genetic interaction networks.
- Using Next Generation Sequencing methods to develop new experimental approaches to investigate gene function and the genomic landscape of C. elegans.
The primary goal for my current fellowship program is to combine and extend my diverse skill sets in bioinformatics, C. elegans, and molecular genetics to the experimentation and analysis of genomic sequence. As massively parallel sequencing (MPS) technologies decrease in cost, it will allow for more endeavours similar in scope to the 1000 Genomes project. Therefore, expertise in the design of experiments that utilize and maximize the capabilities of MPS technologies to answer specific and broad-spectrum health questions will be an asset. Furthermore, in accordance with the rapid expansion of collected human genomic data, experience in bioinformatics analyses will be necessary in deciphering, comprehending, and augmenting our knowledge of genetic networks including their relationships to human genome variants and disease. With these future needs in mind, I am interested in exploring simple and complex genetic interactions from both an experimental and computational aspect. The “Million Mutation Project” (MMP) is the result of collaboration between Dr. Don Moerman (University of British Columbia; large-scale mutagenesis) and Dr. Robert Waterston (University of Washington; massively parallel sequencing) to generate over 2000 mutagenized C. elegans strains. A reagent such as the MMP offers a wealth of data to explore while also providing a means to experimentally verify novel findings. The MMP is at a critical stage where experimental methods must be developed to realize the potential of this resource. There is a clear focus for the initial stages of the project and once these goals are met, the MMP can be applied to many directions of C. elegans research.
My experience with human diseases has given me a great appreciation for the complexity of genetic variants and the role they play in the pathogenesis of disease features. My work in C. elegans has also fostered a deep appreciation for the utility of model genetic organisms, which I see as great assets in both basic and translational research. I am also interested in machine learning techniques and algorithm design and wish to explore this field in terms of genetic interactions and genome sequence analysis. The Waterston group has years of experience developing techniques for sequencing and analyzing genomes and collaborates closely with their Canadian partners the Moerman group to generate high-quality data on the C. elegans genome. Many biological reagents and techniques were developed initially with C. elegans (GFP, genome sequencing, RNAi) and I believe my research and training in the Waterston lab will prove applicable to other model organisms in future projects during the growing genomics era.
My long range career goal is to establish myself as an independent research scientist within a medically-focused institution that is closely linked to human disease research. As a principal investigator my initial goals will be to improve upon the algorithms designed for the MMP projects while also expanding beyond the C. elegans assays I've developed. My goals will also be to focus on aspects of understanding gene function and evolution by studying MMP mutants and the polymorphisms of other nematode isolates. I believe the analysis of C. elegans and other invertebrate models will form the foundation of future studies into the human genome. Extending these applications to human disease gene networks will be challenging but the end results could be very exciting. Ultimately, I hope to contribute to the research of human diseases as a whole through the use of model organisms, bioinformatics, and collaborative efforts involved in elucidating genetic interaction networks.
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