Software
The EnzymeTracker is a web-based laboratory information management system for sample tracking.
Link: http://cubique.fungalgenomics.ca/enzymedb/index.html
Release: v1.0 (June 2010)
Abstract: In many laboratories, researchers store experimental data on their own workstation using spreadsheets. However, this approach poses a number of problems, ranging from versioning or sharing issues to inefficient data-mining. Standard spreadsheets are also error-prone as data do not undergo any validation process. The EnzymeTracker is a flexible and user-friendly alternative that aims at facilitating entry, mining and sharing of experimental biological data. The EnzymeTracker features online spreadsheets and tools for monitoring numerous experiments conducted by several collaborators to identify and characterize samples, from their basic functional annotations to their complete enzymatic activity. It also provides libraries of shared data such as protocols, and administration tools for data access control using OpenID and user/team management. The EnzymeTracker relies on a database management system for efficient data indexing and management and a user-friendly AJAX interface that can be accessed over the Internet. The EnzymeTracker facilitates data entry by dynamically suggesting entries and providing smart data-mining tools to effectively retrieve data. It also features a number of tools to visualize and annotate experimental data, and export customizable reports.
PROFESS is a biology database system that integrates databases describing PROtein Functions, Evolution, Structures and Sequences. PROFESS aims at assisting researchers in the functional and evolutionary analysis of the abundant number of novel proteins continually identified from whole-genome sequencing.
Link: http://cse.unl.edu/~profess/
Release: v1.5 (April 2010)
Abstract: The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are 1100+ molecular biology databases dispersed throughout the Internet. To assist in the functional, structural and evolutionary analysis of the abundant number of novel proteins continually identified from whole-genome sequencing, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database. Our database is designed to be versatile and expandable and will not confine analysis to a pre-existing set of data relationships. A fundamental component of this approach is the development of an intuitive query system that incorporates a variety of similarity functions capable of generating data relationships not conceived during the creation of the database. The utility of PROFESS is demonstrated by the analysis of the structural drift of homologous proteins and the identification of potential pancreatic cancer therapeutic targets based on the observation of protein-protein interaction networks.