Awards

Recognizing the strides and achievements of proteomics researchers.

The CNPN-Tony Pawson Proteomics Award recognizes remarkable achievements on the fundamental understanding and/or practice of proteomics in biological sciences. Formerly called the “CNPN Distinguished Researcher Award”, this award was renamed in 2014 in recognition of the seminal contributions to the proteomics field of one of the most influential Canadian scientists of all time, the late Prof. Tony Pawson, who received the CNPN award in 2013.

Tony Pawson Proteomics Award 2022

The CNPN – Tony Pawson Proteomics Award recognizes remarkable achievements in the fundamental understanding and/or practice of proteomics in biological sciences. Formerly called the “CNPN Distinguished Researcher Award”, the award was renamed in 2014 in recognition of the seminal contributions to the proteomics field of one of the most influential Canadian scientists of all time, the late Prof. Tony Pawson who received the CNPN award in 2013.

Past recipients of the award include: Daniel Figeys (2021), Anne-Claude Gingras (2020), Jennifer Van Eyk (2019), Gilles Lajoie (2018), Pierre Thibault (2017), Michael D. Tyers (2016), Guy Poirier (2015), Christopher Overall (2014), Tony Pawson (2013), Michel Desjardins (2012), Jack Greenblatt (2011) and John Bergeron (2010).

Nominations are open for the 2022 Award (self-nominations are permitted). The award will be presented at the CNPN annual meeting, held in Montreal from May 16-18th, 2022. The awardee will present a lecture on their work and receive an award consisting of a trophy and a $2000 prize.

Applicant Eligibility

  • The applicant must be a Canadian citizen and/or work at a Canadian Institution at the time of application
  • The applicant must be able to receive the award and present a lecture at the 2022 CNPN meeting

How to apply

  • The candidate or sponsor must send a complete pdf application to awards@cnpn.ca before March 29, 2022.
  • The application should consist of:
      • A cover letter briefly describing why the nominee is appropriate for the award; this should include names and email addresses of three supporters who may be contacted by the review committee
      • A brief CV, including the full contact information for the applicant
      • A paragraph suitable for publication on the CNPN website and in the program of the CNPN meeting (see https://cnpn.ca/past-recipients/).
  • We suggest that the applicants also include one page of their “most significant contributions”, similar to the CIHR format.
  • The pdf file and the email header should read: CNPN2022_Pawson _Award_LASTNAME_FIRSTNAME.
  • Incomplete or late applications will not be considered.

The successful applicant will be notified by April 15, 2022.

New Investigator Award 2022

The CNPN – New Investigator Award is a recent initiative of the CNPN to recognize the contributions of an outstanding early career researcher to the fundamental understanding and/or practice of proteomics in the biological sciences. This award will help new investigators gain visibility in the field and encourage early-stage investigators to consider how proteomics may be used in their research.

Past recipients of the award include: Hannes Roest (2021), Jean-Philippe Lambert (2020).

Nominations are open for the 2022 Award (self-nominations are permitted). The award will be presented at the CNPN annual meeting, held in Montreal from May 16-18th, 2022. The awardee will present a lecture on their work and receive an award consisting of a trophy and a $2000 prize.

Applicant Eligibility

  • The applicant must be a Canadian citizen and/or work at a Canadian Institution at the time of application
  • The applicant must be able to receive the award and present a lecture at the 2022 CNPN meeting
  • The applicant will be within the first 6 years of their independent appointment (with consideration for leaves of absence)

How to apply

  • The candidate or sponsor must send a complete pdf application to awards@cnpn.ca before March 29, 2022.
  • The application should consist of: 
      • A cover letter briefly describing why the nominee is appropriate for the award; this should include names and email addresses of three supporters who may be contacted by the review committee
      • A brief CV, including the full contact information for the applicant,
      • A paragraph suitable for publication on the CNPN website and in the program of the CNPN meeting (see https://cnpn.ca/past-recipients/).
      • We suggest that the applicants also include one page of their “most significant contributions”, similar to the CIHR format.
      • The pdf file and the email header should read: CNPN2022_New_Investigator_Award_LASTNAME_FIRSTNAME.
  • Incomplete or late applications will not be considered.

The successful applicant will be notified by April 15, 2022.

2021 CNPN-Tony Pawson Proteomics Award

Dr. Daniel Figeys, University of Ottawa

Dr. Daniel Figeys obtained a B.Sc. and a M.Sc. in chemistry from the Université de Montréal. He obtained a Ph.D. in chemistry from the University of Alberta under the supervision of Dr. Norman Dovichi. He did his postdoctoral studies at the University of Washington in Molecular Biotechnology with Dr. Ruedi Aebersold. Daniel was previously Senior Vice-President at MDS-Proteomics and more recently co-founder of MedBiome. Daniel is a Professor and a Distinguished Research Chair in the Department of Biochemistry, Microbiology, and Immunology at the University of Ottawa. He is the co-founding director of the Shanghai Institute of Materia Medica-University of Ottawa Joint Center in Systems and Personalized Pharmacology and a Chinese Academy of Sciences (CAS) President’s International Fellow. He was the founding director of the Ottawa Institute of Systems Biology. His research focuses on the development and applications of mass spectrometry based bioanalytical technologies to study human health. More recently, his laboratory has been developing technologies and bioinformatic tools to study the human microbiome. Daniel has published over 200 publications were cited more than 17,000 times. Daniel was awarded the 2021 the Ricardo Aroca Award from the Chemical Institute of Canada.

Dr. Daniel Figeys obtained a B.Sc. and a M.Sc. in chemistry from the Université de Montréal. He obtained a Ph.D. in chemistry from the University of Alberta under the supervision of Dr. Norman Dovichi. He did his postdoctoral studies at the University of Washington in Molecular Biotechnology with Dr. Ruedi Aebersold. Daniel was previously Senior Vice-President at MDS-Proteomics and more recently co-founder of MedBiome. Daniel is a Professor and a Distinguished Research Chair in the Department of Biochemistry, Microbiology, and Immunology at the University of Ottawa. He is the co-founding director of the Shanghai Institute of Materia Medica-University of Ottawa Joint Center in Systems and Personalized Pharmacology and a Chinese Academy of Sciences (CAS) President’s International Fellow. He was the founding director of the Ottawa Institute of Systems Biology. His research focuses on the development and applications of mass spectrometry based bioanalytical technologies to study human health. More recently, his laboratory has been developing technologies and bioinformatic tools to study the human microbiome. Daniel has published over 200 publications were cited more than 17,000 times. Daniel was awarded the 2021 the Ricardo Aroca Award from the Chemical Institute of Canada.

2021 New Investigator Award

Dr. Hannes Röst, University of Toronto

The research group of Dr. Röst uses computational approaches to understand clinical phenomena on a personalized level and study biological phenomena from a systems perspective. He develops experimental and computational approaches for mass spectrometry (MS) that drive improved identification and quantification of small molecules and peptide analytes. He specifically focuses on next-generation mass spectrometry approaches using a combination of high mass resolution and fast scan speeds MS to comprehensively acquire information about a biological specimen. In particular, he has developed methods and software for data-independent acquisition (DIA) mass spectrometry, most notably the OpenSWATH and TRIC software which allow automated analysis of SWATH mass spectrometry data. The software is developed as open source and the Rost lab is one of the core developers of the OpenMS C++ framework. In his lab, he combines robust software engineering with advanced signal processing and machine learning methods to extract information from highly multiplexed MS data (specifically DIA data). Dr. Röst applies these methods to acquire comprehensive data about protein or small molecule analytes in complex biological samples such as whole cell lysates or tissue samples. In his lab, he studies cellular systems to gain deeper insight into the exact molecular causes of disease and the genotype to phenotype relationship. Secondly, he uses proteomics and metabolomics approaches in a personalized medicine context to study human subjects in a longitudinal fashion throughout disease progression, specific perturbations and medical interventions. Ultimately, his lab is interested in systematically profiling human specimens in health and disease to gain deeper insight into molecular causes of disease. The SWATH-MS method that he co-developed has been widely adopted in the field and now multiple other MS vendors (Thermo Fisher, Waters, Bruker) are offering the method on their instruments. Dr. Röst is a frequent invited speaker at major international conferences in the field (Dagstuhl (Germany), ASMS (US), HUPO (international), EuBIC (international), US-HUPO (US) and CNPN (Canada)). For his work, Dr. Röst has received the 2018 US HUPO “Gilbert S. Omenn Computational Proteomics Award” for achievements in computational proteomics.

The research group of Dr. Röst uses computational approaches to understand clinical phenomena on a personalized level and study biological phenomena from a systems perspective. He develops experimental and computational approaches for mass spectrometry (MS) that drive improved identification and quantification of small molecules and peptide analytes. He specifically focuses on next-generation mass spectrometry approaches using a combination of high mass resolution and fast scan speeds MS to comprehensively acquire information about a biological specimen. In particular, he has developed methods and software for data-independent acquisition (DIA) mass spectrometry, most notably the OpenSWATH and TRIC software which allow automated analysis of SWATH mass spectrometry data. The software is developed as open source and the Rost lab is one of the core developers of the OpenMS C++ framework. In his lab, he combines robust software engineering with advanced signal processing and machine learning methods to extract information from highly multiplexed MS data (specifically DIA data). Dr. Röst applies these methods to acquire comprehensive data about protein or small molecule analytes in complex biological samples such as whole cell lysates or tissue samples. In his lab, he studies cellular systems to gain deeper insight into the exact molecular causes of disease and the genotype to phenotype relationship. Secondly, he uses proteomics and metabolomics approaches in a personalized medicine context to study human subjects in a longitudinal fashion throughout disease progression, specific perturbations and medical interventions. Ultimately, his lab is interested in systematically profiling human specimens in health and disease to gain deeper insight into molecular causes of disease. The SWATH-MS method that he co-developed has been widely adopted in the field and now multiple other MS vendors (Thermo Fisher, Waters, Bruker) are offering the method on their instruments. Dr. Röst is a frequent invited speaker at major international conferences in the field (Dagstuhl (Germany), ASMS (US), HUPO (international), EuBIC (international), US-HUPO (US) and CNPN (Canada)). For his work, Dr. Röst has received the 2018 US HUPO “Gilbert S. Omenn Computational Proteomics Award” for achievements in computational proteomics.

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