Archive
Research at the Statomics Lab
Overview
At the Statomics Lab, we discover ways to assess complex information relevant to health care, renewable energy, and other applications in the post-genomic era. Improved statistical methods of weighing evidence enable more reliable interpretations of both case-control measurements of genomes and experimental measurements of transcript, protein, and metabolite levels in the cell. A more thorough understanding of these data impacts biomedicine and biotechnology, targeting higher-quality health care and sustainable energy availability.
David Bickel and the trainees in the Statomics Lab are improving statistical methods of weighing evidence to enable more reliable interpretations of both (1) experimental measurements of transcript, protein, and metabolite levels in the cell and (2) case-control measurements of genomes.
Statistical systems biology
In the first component of the research program, the lab is developing statistical methods for the analysis of gene expression microarray data and other functional genomics data. The methods include the creation and testing of new ways to estimate levels of microarray gene expression. For example, this involves work on analogous methods for the case of unpaired data such as that of proteomics and metabolomics platforms and of single-channel microarrays and reliable estimation of the fold change of each gene. Since the emerging field of lipidomics has a need for such methods of data analysis, David Bickel is a mentor in the CIHR Training Program in Neurodegenerative Lipidomics.
Inferring genome-wide associations
For the second component of this research program in high-dimensional statistics, the lab is extending similar methods developed for gene expression data to genome-wide association (GWA) studies, as follows. We are developing and comparing statistical methods of estimating odds ratios while considering concerns about multiple comparisons. In particular, we are inventing shrinkage estimates in the presence of multiple comparisons. We are also creating methods of reliably approximating probabilities of association in order to obtain better point and interval estimates of the effect sizes.
More information
For details on the research summarized above, see the lab’s publications and preprints.
Bioinformatics / neuroinformatics student stipends
Reliable interpretation of genomic and neurological information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com). The Statomics Lab seeks graduate students who will conduct original research involving the application of novel statistical tools to the analysis of transcriptomics, proteomics, metabolomics, genome-wide-association data, and/or neuroscience data.
Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation and good communication skills are also absolutely necessary. The following qualities are desirable but not required: coursework in bioinformatics, computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience with UNIX or Linux.
To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel@uOttawa.ca with the degree sought (either MSc or PhD) and the preferred graduate program (either Biochemistry or Mathematics and Statistics) in the Subject line of the message and with a cover letter in the body of the message. Only those students selected for further consideration will receive a response.
Computational biostatistics student stipends
Reliable interpretation of genomic information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com). The Statomics Lab seeks students who will conduct original research involving the application of novel statistical methods to the analysis transcriptomics, proteomics, metabolomics, and/or genome-wide-association data while earning a graduate degree in Mathematics and Statistics. For information on careers in statistics, see http://tiny.cc/Rqvnf and http://amstat.org/careers/.
Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation, good communication skills, and a degree in bioinformatics, computer science, mathematics, physics, statistics, any field of engineering, or an equally quantitative field are also absolutely necessary. The following qualities are desirable but not required: coursework in computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience with UNIX or Linux.
To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel@uOttawa.ca with the degree sought (MSc or PhD) in the Subject line of the message and with a cover letter in the body of the message. Only those students selected for further consideration will receive a response.
Postdoctoral training in statistical bioinformatics
Reliable interpretation of genomic and neurological information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com). The Statomics Lab seeks a postdoctoral fellow who will collaboratively develop and apply novel methods of statistical inference to attack current problems in analyzing transcriptomics, proteomics, metabolomics, lipidomics, genome-wide-association data, and/or neuroscience data.
A thorough knowledge of computationally intensive statistics is essential, as is the ability to quickly develop reliable software implementing the statistical algorithms developed. Strong initiative, excellent communication skills, and reception of a PhD or equivalent doctorate in bioinformatics, computer science, mathematics, physics, statistics, any field of engineering, or an equally quantitative field within four years prior to the start date are also absolutely necessary. The following qualities are desirable but not required: expertise in bootstrapping and/or constructing accurate confidence intervals; a working knowledge of biology; familiarly with R, S-PLUS, Mathematica, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.
To apply, send a PDF CV that has contact information of three references to dbickel@uOttawa.ca, with “Postdoctoral Fellowship” and the year of your graduation or anticipated graduation in the subject field of the message. In the message body, concisely present evidence that you meet each requirement for the position and describe your most significant papers and software packages with summaries of how you contributed to them. All applicants are thanked in advance; only those selected for further consideration will receive a response.
Research Associate in statistical bioinformatics
Reliable interpretation of genomic and neurological information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com). The Statomics Lab seeks a Research Associate who will collaboratively develop and apply novel methods of statistical inference to attack current problems in analyzing transcriptomics, proteomics, metabolomics, lipidomics, genome-wide-association data, and/or neuroscience data. The successful candidate will also play a key role in the mentorship of junior members of the lab.
A thorough knowledge of computationally intensive statistics is essential, as is the ability to quickly develop reliable software implementing the statistical algorithms developed. A promising publication record, strong initiative, excellent communication skills, and reception of a PhD or equivalent doctorate in bioinformatics, computer science, mathematics, physics, statistics, any field of engineering, or an equally quantitative field are also absolutely necessary. The following qualities are desirable but not required: expertise in bootstrapping and/or constructing accurate confidence intervals; a working knowledge of biology; familiarly with R, S-PLUS, Mathematica, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.
To apply, send a PDF CV that has contact information of three references to dbickel@uOttawa.ca, with “Research Associate” in the subject field of the message. In the message body, concisely present evidence that you meet each requirement for the position and describe your most significant papers and software packages with summaries of how you contributed to them. All applicants are thanked in advance; only those selected for further consideration will receive a response.
Graduate studies in statistical lipidomics
Scientific breakthroughs from genome-sequencing projects brought the realization that reliable interpretation of the resulting information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com). For the CIHR Training Program in Neurodegenerative Lipidomics, the Statomics Lab seeks a graduate student who will develop novel methods of statistical inference and collaboratively use them to discover or validate changes in lipid concentration.
Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation, good communication skills, and a degree in bioinformatics, computer science, mathematics, physics, statistics, any field of engineering, or an equally quantitative field are also absolutely necessary. The following qualities are desirable but not required: coursework in computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience with UNIX or Linux.
To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel0@uottawa.ca (without the zero) with “statistical lipidomics graduate student” in the Subject line of the message. In the message body, specify the graduate program in which you wish to take courses (either Biochemistry or Mathematics and Statistics) and the degree sought (MSc or PhD). Only those students selected for further consideration will receive a response.
Postdoctoral training in Bayesian genomics
Scientific breakthroughs from genome-sequencing projects brought the realization that reliable interpretation of the resulting information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statistical Inference and Computation in Genomics Laboratory of the Ottawa Institute of Systems Biology. The Statomics Lab (http://www.statomics.com) seeks a postdoctoral fellow who will collaboratively develop and apply Bayesian methods of statistical inference to attack current problems in analyzing transcriptomics, proteomics, metabolomics, lipidomics, and/or genome-wide association data.
A thorough knowledge of Bayesian theory is essential, as is the ability to quickly develop reliable software for approximating posterior distributions using complex models. Strong initiative, excellent communication skills, and reception of a PhD or equivalent doctorate in biostatistics, statistics, or a closely related field within the four years prior to the start date are also absolutely necessary. The following qualities are desirable but not required: expertise in one or more methods of frequentist inference; a working knowledge of biology; familiarly with R, S-PLUS, Mathematica, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.
To apply, send a PDF CV that has contact information of three references to dbickel0@uottawa.ca (without the zero), with “Bayesian Genomics” and the year of your graduation or anticipated graduation in the subject field of the message. In the message body, concisely present evidence that you meet each requirement for the position and describe your most significant papers and software packages with summaries of how you contributed to them. All applicants are thanked in advance; only those selected for further consideration will receive a response.
Postdoctoral training in model selection & applications
Scientific breakthroughs from genome-sequencing projects brought the realization that reliable interpretation of the resulting information makes unprecedented demands for advances in statistical methodology. As the complexity of genomic data sets drives innovative research in statistics, the Statistical Inference and Computation in Genomics (Statomics) Lab of the Ottawa Institute of Systems Biology attacks inferential challenges of importance to human health. The lab seeks a postdoctoral researcher who will collaboratively develop and apply statistical methods of model selection to solve current problems in analyzing transcriptomics, proteomics, metabolomics, lipidomics, and/or SNP-chip data.
A thorough knowledge of statistical theory is essential, as is the demonstrated ability to quickly and accurately implement complex statistical methods in software. Strong initiative, excellent communication skills, and reception of a PhD or equivalent doctorate in biostatistics, statistics, or a closely related field within the four years prior to the start date are also absolutely necessary. The following qualities are desirable but not required: expertise in one or more methods of frequentist model selection; knowledge of biology; familiarly with R, S-PLUS, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.
To apply, send a PDF CV that has contact information of three references to dbickel0@uottawa.ca (without the zero), with “model selection & applications” and the year of your graduation or anticipated graduation in the subject field of the message. In the message body, concisely present evidence that you meet each requirement for the position and describe your most significant papers and software packages with summaries of how you contributed to them. All applicants are thanked in advance; only those selected for further consideration will receive a response.
Bioinformatics graduate program
Ottawa-Carleton MSc/MCI Program in Bioinformatics
David Bickel is currently accepting new students.
For more information on the field of bioinformatics, see the slides from the First Canadian Workshop on Statistical Genomics, the links provided by Georgia Tech, and the jobs posted at the Canadian Bioinformatics Workshops.
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