Google Summer of Code 2014: Co-authorship social network App
Short Description (from Cytoscape GSoc wiki)
Create a visual summary of how individuals are connected
Biological networks can be visualized and analyzed using Cytoscape. Often researchers want to go beyond the network of proteins or genes and also look at the inter-connectedness between colleagues and institutions. Who tends to publish together? What institutions are most collaborative? Are there inter-disciplinary connections in my institution?
Goal:An existing App currently queries PubMed directly or takes in a file with a set of publications (from scopus or incites) and builds a co-publication network where nodes are authors and edges the number of publications two authors share. Different sources have different depths of data, for instance PubMed, the most widely accessible of the three main sources, has citation counts but they are limited to only those articles cited in pubmed central and its institution data is limited to the first author. Given that PubMed is the most accessible source we want to expand its functionality to include computed institution data as well as better citation count approximations, and H-index calculation for individuals or subsets of papers.
This functionality can be applied to several data types outside academia, whenever relationships between people is of interest. An example is professional social networks (e.g. linked-in), where individuals are connected by who they have worked with in the past or the twitter-verse where individuals are connected when they each reference the same (#) hash tag. This project will start with support for co-publication networks and extend to other networks like twitter and linked-in as time permits. Additionally, we want to expand our co-authorship cytoscape App to include generic file formats to easily create the above networks.
Language and Skills
Java, XML, PubMed e-utils
Example input file
Three different ways to create the same network:
- Use the app internal capability to search pubmed and search for "Bader GD"
Example scopus data file - scopus_example_gdb.csv
Going Beyond Simple Solutions
We would like applicants to be creative, and come up with new or different ways to generalize their proposed app so that it is applicable for more than just publications.
We are part of Gary Bader's lab at University of Toronto - CCBR (Toronto, ON Canada). Our lab is strongly engaged in biological network research. Feel free to have a look at our home page for more details on the lab research areas, and at our home-pages for our own research interests.