Networks in Biological Sciences
(1 June - 31 July 2015)

Jointly organized with Department of Mathematics, NUS

Organizing Committee · Visitors and Participants · Overview · Activities · Venue

 

Organizing Committee

 

Chair

• Louxin Zhang (National University of Singapore)

 

Members

• Xin Chen (Nanyang Technological University)
• Kwok Pui Choi (National University of Singapore)
• Frank Eisenhaber (Bioinformatics Institute)
• Luay K. Nakhleh (Rice University)
• Gesine Reinert (Oxford University)
• Mike Steel (University of Canterbury)
• Greg Tucker-Kellogg (National University of Singapore)
• Lusheng Wang (City University of Hong Kong)

 

Visitors and Participants

 

• Overseas visitors
• Local visitors
• Graduate students
• Registered local participants

 

Overview

 

With high-throughput technology for genome and peptide sequencing, biology is moving towards a quantitative science. In recent years, many fundamental biologists have become adept at using mathematical and computational tools to analyze and model biological processes. Simultaneously, a plethora of mathematicians, physicists, and computer scientists have committed fully to apply their quantitative skills to discover new biology.

The proposed program will focus on mathematics for network models in biology. After a wide variety of genomes have been fully sequenced and annotated, networks of different types have been used to study cellular biological processes as well as genetic diseases. In this network view, each node represents a molecule, such as a gene, RNA or protein, or an organism. The edge between two nodes represents a relationship, such as an enzymatic reaction, physical interaction, a transcriptional regulation, or an evolutionary relationship. It has been repeatedly demonstrated that protein interaction information is very useful for determining specific functions of proteins, classifying cell lineages, and identifying valuable biomarkers for disease classification and diagnosis. 

Network models are also found in evolutionary biology. Since Darwin, a phylogenetic tree has been the principle mathematical structure for the presentation and study of the origin and diversification of species. Phylogenetic trees have been often reconstructed from DNA or protein sequences since the sequence information became available in 1960s.  However, a number of evolutionary processes lead to non-tree patterns of evolutionary relationships among genetic components of species and even of the species themselves: genetic recombination, gene conversion between paralogs, incomplete lineage sorting, unequal rates of character loss between lineages, to name just a few.  The use of a tree model simply oversimplifies a complex evolutionary process and hence networks that are more general than trees are sought to study genetic restructuring and non-vertical transfer. 

 

One focus of our program is to bring together researchers in complex networks and systems biology to enable knowledge transfer in the study of cellular networks. Analyses of dynamic and topological properties of complex networks have produced insightful concepts which should be very useful in systems biology; on the other hand, systems biology provides interesting questions and ideas for complex network analysis.

 

Another focus of our program is systematic methods for phylogenetic networks. In the study of evolution, network provides biological explanations that go beyond what can be accommodated by the tree model. However, network modeling is extremely challenging. It offers outstanding opportunities for mathematicians and statisticians.  Mathematics is needed to develop fast and robust programs for inferring an evolutionary network model from sequence data. Statistical methods are required to distinguish genuine horizontal genetic transfers from background noise such as incomplete lineage sorting.  

Activities

 

• Tutorial I: 3 - 5 Jun 2015
• The Protein Network Workshop: 8 - 12 Jun 2015
• Seminars

	Jointly organized with Department of Statistics and Applied Probability
	Date:	Tuesday, 7 July 2015
	Venue:	Block S16-06-118, DSAP Seminar Room, Department of Statistics and Applied Probability, Faculty of Science, NUS
	1:00pm - 2:00pm	Ancestry estimation and control of population structure in genetic association studies Chaolong Wang, Genome Institute of Singapore
	Date:	Friday, 24 Jul 2015
	Venue:	IMS Auditorium
	11:00am - 12:00nm	Integrating biological networks into statistical models: from static to dynamic interaction networks Hyungwon Choi, National University of Singapore

• Tutorial II: 22 - 24 Jul 2015
• The Phylogenetic Network Workshop:  27 - 31 Jul 2015

 

Please note that our office will be closed on the following public holidays.

- 1 Jun 2015, Vesak Day
- 17 Jul 2015, Hari Raya Puasa

 

Students and researchers who are interested in attending these activities are requested to complete the online registration form.

The following do not need to register:

• Those invited to participate.

 

Venue

 

• IMS Auditorium
   

Organizing Committee · Visitors and Participants · Overview · Activities · Venue