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A history of all news can be found [[History | here]].
 
A history of all news can be found [[History | here]].

Revision as of 14:34, 15 December 2011



NEWS
» Tim
[[Category:Homepage]]

__NOTOC__

header=[[History|NEWS]]|limit=3 {{#css:/cbg/skins/bulletins.css}} A history of all news can be found [[History | here]].

== Welcome to the ''Computational Biology Group'' (CBG) at the ''[http://www.unil.ch/dgm/page13525.html Department of Medical Genetics]'' of the [http://www.unil.ch University of Lausanne]! ==

[[Image:CBG picture 2010.jpg|thumb|Photo by Nicolas Righetti|500px]]

We have interest in various fields related to Computational Biology, which are detailed in the [[Science]] section of this wiki. Briefly, there are two main directions: We develop and apply methods for the integrative analysis of large-scale biological and clinical data. This includes ''molecular'' phenotypes like gene-expression data, as well as ''organismal'' phenotypes (ranging from patient data to growth arrays). We focus particularly on relating these phenotypes to genotypes such as "Single Nucleotide Polymorphisms" (SNPs) and "Copy Number Variants" (CNVs) measured by microarrays or next-generation sequencing. Our goal is to move towards predictive models in order to improve the diagnosis, prevention and treatment of disease. A complementary direction of research pertains to relatively small genetic networks, whose components are well-known. We collaborate closely with experts of the field to identify biological systems that can be modeled quantitatively. Our goal in developing such models is not only to give an approximate description of system, but also to obtain a better understanding of its properties. For example, regulatory networks evolved to function reliably under ever-changing environmental conditions. This notion of robustness can guide computational analysis and provide constraints on models that complement those from direct measurements of the system's output.

In general, our group seeks an interdisciplinary approach, bridging the traditional gaps between physics, mathematics and biology. Our lab collaborates with experimental groups within and outside our department. In particular, due to our proximity to the CHUV we have close contacts to medical research groups and assist the analysis of clinical data.

== General info on this wiki ==

This wiki is the main instrument to centralize and archive information on and generated by the CBG. [mailto:wwwcbg@unil.ch Drop an email to the admin] if you have any questions or need an account.
1 Oct 2014 — 16:10
[[Category:Homepage]]

__NOTOC__

header=[[History|NEWS]]|limit=3 {{#css:/cbg/skins/bulletins.css}} A history of all news can be found [[History | here]].

== Welcome to the ''Computational Biology Group'' (CBG) at the ''[http://www.unil.ch/dgm/page13525.html Department of Medical Genetics]'' of the [http://www.unil.ch University of Lausanne]! ==

[[Image:CBG picture 2010.jpg|thumb|Photo by Nicolas Righetti|500px]]

We have interest in various fields related to Computational Biology, which are detailed in the [[Science]] section of this wiki. Briefly, there are two main directions: We develop and apply methods for the integrative analysis of large-scale biological and clinical data. This includes ''molecular'' phenotypes like gene-expression data, as well as ''organismal'' phenotypes (ranging from patient data to growth arrays). We focus particularly on relating these phenotypes to genotypes such as "Single Nucleotide Polymorphisms" (SNPs) and "Copy Number Variants" (CNVs) measured by microarrays or next-generation sequencing. Our goal is to move towards predictive models in order to improve the diagnosis, prevention and treatment of disease. A complementary direction of research pertains to relatively small genetic networks, whose components are well-known. We collaborate closely with experts of the field to identify biological systems that can be modeled quantitatively. Our goal in developing such models is not only to give an approximate description of system, but also to obtain a better understanding of its properties. For example, regulatory networks evolved to function reliably under ever-changing environmental conditions. This notion of robustness can guide computational analysis and provide constraints on models that complement those from direct measurements of the system's output.

In general, our group seeks an interdisciplinary approach, bridging the traditional gaps between physics, mathematics and biology. Our lab collaborates with experimental groups within and outside our department. In particular, due to our proximity to the CHUV we have close contacts to medical research groups and assist the analysis of clinical data.

== General info on this wiki ==

This wiki is the main instrument to centralize and archive information on and generated by the CBG. [mailto:wwwcbg@unil.ch Drop an email to the admin] if you have any questions or need an account.
15 Apr 2014 — 11:04
[[Category:Homepage]]

__NOTOC__

header=[[History|NEWS]]|limit=3 {{#css:/cbg/skins/bulletins.css}} A history of all news can be found [[History | here]].

== Welcome to the ''Computational Biology Group'' (CBG) at the ''[http://www.unil.ch/dgm/page13525.html Department of Medical Genetics]'' of the [http://www.unil.ch University of Lausanne]! ==

[[Image:CBG picture 2010.jpg|thumb|Photo by Nicolas Righetti|500px]]

We have interest in various fields related to Computational Biology, which are detailed in the [[Science]] section of this wiki. Briefly, there are two main directions: We develop and apply methods for the integrative analysis of large-scale biological and clinical data. This includes ''molecular'' phenotypes like gene-expression data, as well as ''organismal'' phenotypes (ranging from patient data to growth arrays). We focus particularly on relating these phenotypes to genotypes such as "Single Nucleotide Polymorphisms" (SNPs) and "Copy Number Variants" (CNVs) measured by microarrays or next-generation sequencing. Our goal is to move towards predictive models in order to improve the diagnosis, prevention and treatment of disease. A complementary direction of research pertains to relatively small genetic networks, whose components are well-known. We collaborate closely with experts of the field to identify biological systems that can be modeled quantitatively. Our goal in developing such models is not only to give an approximate description of system, but also to obtain a better understanding of its properties. For example, regulatory networks evolved to function reliably under ever-changing environmental conditions. This notion of robustness can guide computational analysis and provide constraints on models that complement those from direct measurements of the system's output.

In general, our group seeks an interdisciplinary approach, bridging the traditional gaps between physics, mathematics and biology. Our lab collaborates with experimental groups within and outside our department. In particular, due to our proximity to the CHUV we have close contacts to medical research groups and assist the analysis of clinical data.

== General info on this wiki ==

This wiki is the main instrument to centralize and archive information on and generated by the CBG. [mailto:wwwcbg@unil.ch Drop an email to the admin] if you have any questions or need an account.
5 Mar 2014 — 16:03

{{#css:/cbg/skins/bulletins.css}} A history of all news can be found here.

Welcome to the Computational Biology Group (CBG) at the Department of Medical Genetics of the University of Lausanne!

Photo by Nicolas Righetti

We have interest in various fields related to Computational Biology, which are detailed in the Science section of this wiki. Briefly, there are two main directions: We develop and apply methods for the integrative analysis of large-scale biological and clinical data. This includes molecular phenotypes like gene-expression data, as well as organismal phenotypes (ranging from patient data to growth arrays). We focus particularly on relating these phenotypes to genotypes such as "Single Nucleotide Polymorphisms" (SNPs) and "Copy Number Variants" (CNVs) measured by microarrays or next-generation sequencing. Our goal is to move towards predictive models in order to improve the diagnosis, prevention and treatment of disease. A complementary direction of research pertains to relatively small genetic networks, whose components are well-known. We collaborate closely with experts of the field to identify biological systems that can be modeled quantitatively. Our goal in developing such models is not only to give an approximate description of system, but also to obtain a better understanding of its properties. For example, regulatory networks evolved to function reliably under ever-changing environmental conditions. This notion of robustness can guide computational analysis and provide constraints on models that complement those from direct measurements of the system's output.

In general, our group seeks an interdisciplinary approach, bridging the traditional gaps between physics, mathematics and biology. Our lab collaborates with experimental groups within and outside our department. In particular, due to our proximity to the CHUV we have close contacts to medical research groups and assist the analysis of clinical data.


General info on this wiki

This wiki is the main instrument to centralize and archive information on and generated by the CBG. Drop an email to the admin if you have any questions or need an account.