Aim of Research Project
My research project aims to extend upon the original PATHLINKER paper. In particular, I hope to investigate different weighting schemes both from the perspective of utilizing different data sets and data-summary methods as well as potentially maybe different statistical tools for manipulating the data in meaningful ways. This is motivated by the fact that there appears to be little overlap between interactomes consisting of the same proteins but weighted differently. Therefore, this project will allow us to analyze different schemes and develop an heuristic for weighting interactomes. As a result, we will be able to apply algorithms like PATHFINDER on graphs such that they provide results that have valid biological meaning rather than being affected by superficial factors such as trends in scientific research or biases of the scientific community. Right now, I am focusing on Bayesian Weighting schemes which attempt to use experimental evidence to provide a weight that represent the probability of a given interaction occurring in a given signaling pathway by leveraging Bayes’ theorem. I will talk more about this in future posts.
Week 1 Progress
Week 1 was spent mostly acquainting myself with the necessary prerequisite knowledge required for research during coming weeks such as Dijkstra’s algorithm (and its implementation) and Bayesian Weighting Schemes and in that regard reading some relevant papers. For the sake of keeping track the particular papers were titled :-
- Pathways on demand: automated reconstruction of human signalling networks
- Top-Down Network Analysis to Drive Bottom-Up Modeling of Physiological Processes
- Bridging high-throughput genetic and transactional data reveals cellular responses to alpha-synuclein toxicity.
The first was the original PATH LINKER paper which our research hopes to extend upon. The next two provided some information on Bayesian Weighting but did not provide too much else due to some ambiguous mathematical notation. I hope to attempt to write a document that annotates the relevant portions of the papers for the sake of clarity and future reference.