Peer Groups
Peer groups are informal groups of researchers using a similar methodology, or working on a similar topic, who interact regularly to exchange information, critically follow new developments, and come up with innovative solutions to problems. Peer groups operate on an ad hoc basis depending on the present composition of the centre and on current projects. They also include colleagues in the wider UM community.
The following peer groups have operated, or regularly operate:
- RNA-seq data analysis (contact Michiel Adriaens)
- Network Biology (contact Martina Summer-Kutmon)
- Computational models and complex systems in neuroscience (contact Renaud Jolivet)
- Microbiome data analysis (contact David Barnett)
Please do not hesitate to contact us if you would like to join an existing peer group, or to start a new one.
RNA-seq data analysis<a id="rna" name="rna"></a>
These monthly meetings on the specialised topic of RNA-sequencing data analysis aims to present new and ongoing RNA-sequencing research within Maastricht University, with a focus on challenges encountered during data analysis.
Due to the specialised nature of the meeting, participation is limited to researchers who are directly involved in the processing, analysis and other technical aspects of RNA-sequencing data.
Organising Committee: Michiel Adriaens
Network Biology <a id="networkbiology" name="networkbiology"></a>
The purpose of this peer group is to connect researchers at Maastricht University who are applying network biology in their research. The group allows us to share experiences and challenges as well as introduce new and existing tools and applications of network analysis and visualisation in the study of biology and medicine.
In the past few years, the application of networks to study the complexity of biological systems has been rapidly developing and has made advances towards a better understanding of the structure and dynamics at play.
The study of networks has emerged in diverse disciplines as a means of analysing complex data. The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualisation from computer science, inferential modelling from statistics, and social structure from sociology.
Organising Committee: Martina Summer-Kutmon
Computational models and complex systems in neuroscience <a id="computational" name="computational"></a>
This group aims at bringing together researchers and practitioners using a similar methodology or working on a similar topic in areas related to complex systems and computational models.
Researchers and scientists from mathematics and computer science as basic computing disciplines, researchers from various application areas who are pioneering computational methods in sciences such as physics, life sciences, and engineering will discuss problems and solutions in the neuroscience area, identify new issues, and shape future directions for research. In order to interact regularly to exchange information and critically follow new developments, participants are expected to share their work experience in turn, in organised monthly meetings.
Due to the specialised nature of the meeting, participation is limited to researchers who are directly involved in the processing, analysis and other technical aspects of the specific topic will be discussed.
Organising Committee: Renaud Jolivet
Microbiome data analysis<a id="microbiome" name="micriobiome"></a>
This group aims to connect researchers who work with microbial community data, or intend to do so. Particularly human/other host-associated microbiota.
The analysis of microbial community data, such as that from 16S gene amplicon or shotgun metagenomic sequencing methods, is a complex, specialised and fast-moving field. The latest bioinformatics and statistical methods for processing and analysing microbiome data will be discussed and experiences with these methods will be shared.
Organising Committee: David Barnett