The Applied Bioinformatics Lab (ABL) at the University of Kansas is a research-oriented service laboratory providing advanced and comprehensive informatics support to the research community. Currently ABL staff focus on the followings:
- Data analysis and mining in proteomics, genomics and chemistry;
- Systems biology approaches such as pathway, network and interaction analyses;
- Large scale statistical and machine learning studies;
- Protein structure, function and stability prediction, sequence and domain analyses;
- Design and implementation of relational databases and software programs;
- Consultation on experimental design involving data acquisition, management and analysis;
- Report, grant, and manuscript preparation.
Services are provided in the form of fee-based consultation for well defined informatics analysis, or collaborative projects for those requiring longer-term commitment of time and effort. We also provide workshops and one-to-one sessions for training in software programming and data analysis. We constantly explore new informatics areas and building new capacities based on scientific trends and local needs.
Free Weekly Bioinformatics Walk-in Hour
2 pm - 3 pm, Wednesday
Room 1014, Structural Biology Center, west campus
It is on a first-come-first-serve basis and so no appointment is required. The walk-in hour was designed as a resource for researchers who only need informal input
or help on simple questions. Faculty, staff, fellows and students are all welcome to stop by. You can certainly make an appointment with
us
for other time.
Contact
Jianwen Fang, Ph.D.
Director, Applied Bioinformatics Laboratory
Office: 1014 Structural Biology Center
Phone: (785) 864-3349
Email: jwfang@ku.edu
Pricing and Grant policy
We rely on service fees to recoup operating
expenses, purchase and maintain hardware/software. Typically,
funding support is required via hourly rates, or arranged as a
percent effort of sponsored research. However, The initial consulting
session (~ of up to one hour) is available at no charge for a new project.
Authorship policy
Co-authorship on scientific articles is generally
expected on studies where substantive input on experimental design
and data analysis is provided. It is our policy not to forego funding
in return for co-authorship. The official MSG policy is available
here.