#BIG2016
Speakers
LYNNE QUARMBY
KEYNOTE SPEAKER
Lynne Quarmby is a professor of Molecular Biology & Biochemistry at Simon Fraser University. Her research on the relationship between cilia and cell cycle regulation has made extensive use of the unicellular green alga, Chlamydomonas reinhardtii. Recently, she turned her attention to Chlamydomonas nivalis, the alga most often associated with red snow, studying its role in the positive feedback loops accelerating the melting of Arctic snow and ice. Lynne is politically active, advocating for science and for environmental and social justice.
Engaging the public: lessons from the frontlines
She was sued by pipeline giant Kinder Morgan and was twice arrested for civil disobedience. In the 2015 federal election Lynne ran as the Green Party candidate in Burnaby North – Seymour and she currently serves at the Science Critic for the Green Party of Canada.
Dr. Quarmby’s talk will focus on exploring the question of how scientists can most effectively engage with a public that frequently feels overwhelmed by conflicting information. People often don’t know what to think or who to believe. From climate change to GMOs to Zika virus, so-called experts abound and the public is often unable to distinguish science from pseudoscience. The problem goes beyond scientific literacy and beyond adding our voices to the cacophony of competing experts.
Download the talk's presentation
DAVID NG
WORKSHOP SPEAKER
Insights from the interdisciplinary boundaries of science
David Ng, who looks after the Advanced Molecular Biology Laboratory, a science literacy unit within the Michael Smith Labs, will run a session that highlights the importance of interdisciplinary thinking, both in terms of your career and in your role as an engaged citizen. Here, he'll use his experiences in advocacy, communications, education, policy work, and developing world programs, to examine how your work and identity as scientists mesh with social science and artistic contexts.
From here, he'll make a case for the importance of being comfortable in these interstitial spaces, both in terms of career opportunities as well as being better equipped to contribute to society in a more engaged manner.
Bio: David Ng is a geneticist, science educator, and faculty based at the UBC Michael Smith Laboratories. He is Director of the Advanced Molecular Biology Lab (AMBL), which is a fully equipped research lab that specializes in educational programs and is in the fortunate position of being resourced to provide a superb learning environment complete with state of the art equipment. In all, many of AMBL’s programs centre on a mandate to train scientists (university students, faculty, and industry professionals) and to inform the public at large on the societal, cultural, economic, political, and ethical nuances of the sciences. David is also supervising a number of research projects that look at various areas of science literacy - in particular, those that explore notions of science and creativity, as well as the use of game-based learning in STEM.
Of note: (1) he is partly responsible for the massive DNA helix emblazoned on his building’s facade; (2) his Dad beat up Bruce Lee; (3) his first foray into general publishing featured a unicorn on the front cover; and (4) his lab studies things like Pokemon and creativity. Learn more at bioteach.ubc.ca
MARTIN KRZYWINSKI
WORKSHOP SPEAKER
The art and science of data visualization: drawing (inferences from) your research
From fashion photography to visualizing the deadly genomes - Martin Krzywinski has acquired a diverse portfolio in design and visualization in his quest to combine science with art. Martin is currently a staff scientist at the Genome Sciences Centre, and quite well known in bioinformatics circles for creating Circos (pun intended). Martin’s recent work has focused on visualizing networks in a quantitative manner (hive plots), helping scientists compare and contrast large and complicated networks - while ‘keeping your sanity’ at the same time. He has also been involved with numerous creative projects at the intersection of science and graphics art (mkweb.bcgsc.ca/pi/). In this workshop, Martin will be talking about his experiences with the development of visualization tools in the sciences, and the confluence of art and science in his work. Come learn how to approach a scientific problem from an artistic perspective!
Martin is inviting prospective participants to send in self-created visualizations (pertaining to their research).
He will be redesigning one lucky visualization and presenting his approach to the process in the workshop.
MICHAEL SJOERDSMA
WORKSHOP SPEAKER
Starting a sentence with because and other things you may do: Exploring the myths of technical writing
This seminar will explore various myths regarding technical writing and the reasons for adopting a strategies-based approach. Understanding the writing process sets the foundation from moving from rules to strategies.
Bio: Michael Sjoerdsma is a Senior Lecturer in the School of Engineering Science at Simon Fraser University and the coordinator of the technical communication program. Michael teaches a number of courses encompassing various aspects of
technical communication: Form, Style and Professional Genres; Graphical Communication for Engineering; Spatial Thinking and Communicating; Project Documentation and Team Dynamics; Social Responsibility and Professional Practice; and Human Factors and Usability. In addition to his teaching, Michael consults in industry regarding technical communication, and he is a volunteer mentor for a non-profit organization that helps integrate new immigrants to the Canadian work force.In collaboration with Agriculture Canada, his undergraduate honors thesis focused on creating a rapid pathogen detection system used for greenhouse plants. His Master’s thesis, in partnership with Auto21, focused on the semi-active control of structure-borne noise in automobiles. Michael also has a certificate in Teaching English to Speakers of Other Languages (TESOL). Currently, Michael is a candidate for the degree of Doctor of Education, where he is using soft systems methodology to study engineering education.
JAMES TOPHAM
TECH-TALK
Machine Learning Approaches in NGS Data Analysis
Machine learning represents a powerful application of artificial intelligence in which algorithms are capable of learning trends within data to predict or classify novel observations.
Several approaches provide a means by which to approach big data, through identification of specific variables responsible for driving a statistical trend within the data. In this way,
machine learning is able to complement many routine next-generation sequencing analyses. In this presentation, I frame concepts of machine learning within a context specifically
geared towards the analysis of large biological datasets. Emphasis will be placed on decision tree and linear regression techniques, with examples combining statistical, computational
and biological perspectives serving to aid in providing researchers with a head-start in the incorporation of machine learning techniques in their large scale biological analyses.
KARISSA MILBURY
TECH-TALK
Identification of genetic interactions with
high-throughput synthetic genetic array analysis
Synthetic genetic array (SGA) is a high-throughput technology that allows us to query a mutant of interest against extensive mutant collections of S. cerevisiae for synthetic growth defects. This technology has been used to map gene interaction networks, test gene dosage hypotheses, and introduce fluorescently marked alleles for rapid phenotyping. Although it cannot handle human cells, SGA can be used to ask health-relevant questions due to the large similarities between yeast and human genetics.
KENT CHEN
TECH-TALK
Liposome Technology: evolution from model membrane systems to drug delivery solutions
Liposomes are small (100-times smaller than a red blood cell) structures comprising a lipid bilayer surrounding an aqueous core. They were initially developed as a model membrane system that could be used to uncover the functional roles of lipids in membranes as well as facilitating a greater understanding of how membrane proteins interact with lipid bilayers. As such, the usefulness of liposomes as models to study various properties of biological membranes such as trans-membrane transport and membrane permeability was recognized early on. Some ten years later, liposomes proved useful to protect compounds and proteins from degradation. Finally the utility of liposomes to act as nano-scaled delivery systems was explored. Most molecular biologists are familiar with the use of liposomes as reagents to facilitate transfer of plasmid expression vectors, antisense oligonucleotides, siRNA and mRNA into cells. However, one of the research areas that led to development of improved anticancer drugs concerned the use of liposomes as drug delivery vehicles. The dose of many chemotherapeutic agents is limited due to unacceptable toxicities, i.e. the dose required to achieve desired anti-tumour activities is often toxic to normal cells. An elegant solution to this problem would be to provide “targeted” therapy and enhanced selectivity of the anti-cancer drug of interest – liposomes provide such a solution. Due to the leaky nature of tumour associated blood vessels and poor lymphatic drainage the tumour environment facilitates accumulation and retention of drug loaded liposomes. Further, liposomes can be modified to direct the associated drug to cell populations within the tumor. My presentation will focus on liposome technology with the goal of providing some insight into their use for biological applications that have led to an improved understanding of cancer as well as approved therapeutics that are providing significant benefits to patients.
SHAUN JACKMAN
TECH-TALK
Using Make to automate data analysis pipelines
Bioinformatics analysis often involves designing a pipeline of commands and running that pipeline on many data sets. There are many ways to tackle this common task. Running commands interactively at the command line has the downside of being terribly unreproducible, unless one’s memory is fantastically infallible. Recording the commands in a shell script certainly beats storing the commands in one’s leaky brain, but is not particularly well suited to resuming the pipeline at a particular point, as is necessary after making a change to one step of the pipeline, nor to running independents steps in parallel. The venerable UNIX Make program is surprisingly well suited to describing bioinformatics pipelines. Make can resume a pipeline after a failed command without needing to start over, and it runs independent jobs in parallel. A Makefile describes a pipeline of shell commands and the interdependencies of the input and output files of those commands. A Makefile can be easily displayed as a graphical flow chart of files and shell commands, and such a visualization is a pleasing and powerful way to interpret a pipeline oneself or to communicate a pipeline to a collaborator.