DESCRIPTION: AutomN is concerned with automating the tedious task of protein interaction pathway discovery using only protein sequences as input. AutomN wraps many bioinformatics tools into one easy to use, streamlined package. AutomN is entirely GUI-based, making it so that the user can immediately point and click to select the options they want instead of having to consult long manuals in order to find a specific command line switch they desire. AutomN uses a pipeline architecture, meaning that bioinformatics analysis tools are called one after another on a set of data, continually transforming it until the desired result is achieved. AutomN takes two protein sequences as input and attempts to locate a structure for each sequence using BLAST. If no structure is found, the structure is predicted using Rosetta. Once the structure is defined for both input proteins, they are docked together using ZDOCK. The optimal predictions from the ZDOCK run are then displayed to the user in a graphical format so he or she can decide which interactions are worth further study. ABSTRACT: One of the goals of the structural bioinformatics field is to discover how a protein's sequence determines its structure and how these protein structures interact with each other. A plethora of tools that tackle specific areas of this problem have been developed and focus primarily on protein docking, homology modeling and threading, structure prediction, and similarity comparison. Unfortunately, the use of several of these non-intuitive and user un-friendly tools are required for the simplest research project. The learning curve of these tools and repetitious tasks required to operate them consume massive quantities of researcher time. AutomN seeks to eliminate this by automatically wrapping many of these tools in an easy to use GUI and automating the entire process. Figure 2 CONCLUSION: AutomN is a new bioinformatics tool that uses a pipeline architecture to automate the process of converting two protein sequences into an ensemble of probable docked protein complexes. By understanding which proteins interact with others, it becomes possible to modify these interactions with newly created drugs and to better understand the inner workings of all organisms. The AutomN team hopes to increase throughput of any research-oriented organization and broaden the user base of sophisticated research tools. In addition, AutomN is so easy to use that almost any student can utilize it, making it a candidate as a learning tool. The main goals of this tool are to save time by automating repetitive research tasks and to allow users with limited knowledge of modeling techniques to accomplish quite complex tasks. For our first version, AutomN does not implement any new bioinformatics algorithms, but focuses on making existing algorithms easier to use. AutomN has great potential in the research and learning community. Hopefully with a few years of continued work, AutomN will become commonplace in the arsenal of widely available bioinformatics tools. FUTURE WORK: For subsequent versions, our focus will be directed toward allowing AutomN to utilize any bioinformatics algorithm in our problem domain. This adaptable plug-in architecture ensures the user is not tied to a particular analysis module. Also, AutomN should be able to detect if a module has failed and be able to recover from the error gracefully. Lastly, advanced analysis routines which help the researcher determine the validity of the docked structures will be added. Figure 3 Figure 1: AutomN’s Graphical User Interface Figure 2: Data Flow through the AutomN Pipeline Figure 3: AutomN generated docked structure of PDB 1A15 and 1CRN Note: AutomN is a play on the words autumn and automatic. Figure 1 This project was developed in Spring 2005 as part of the course CS 426 Senior Projects Advisors: Dr. Brian W. Beck 1, Dr. Sergiu Dascalu 2, and Brian Westphal 2 Department of Biochemistry 1, CSE Department 2, UNR