Project description: One of our projects is an implementation of an integrated biological information website that classifies technical documents, learns about users' interests, and offers intuitive interactive visualization to navigate vast bioinformatics information spaces. Straightforward yet powerful document characterization strategies are illustrated, helpful visualization for effective knowledge transfer is shown, and current user interface methodologies are applied. A specific success of note is the collaboration of disparately skilled specialists to deliver a flexible integrated prototype in a rapid manner that meets user acceptance and performance goals. The domain chosen for the demonstration is breast cancer, using a corpus of abstracts from publications obtained online from Medline. The terms in the abstracts are extracted by word stemming and a stop list, and are encoded in vectors. A TF-IDF technique is implemented to calculate similarity scores between a set of documents and a query. Polysemy and synonyms are explicitly addressed. Groups of related and useful documents are identified using interactive visual displays such as a spiral graph that represents of the overall similarity of documents. K-means clustering of the similarities among a document set is applied to display a 3-D relationship map.

 

Publications:

2004 Min Hong, Anis Kairmpour-fard, Steve Russell, and Lawrence Hunter, “Integrated Term Weighting, Visualization, and User Interface Development for Bioinformation Retrieval”, AI, Simulation and Planning in High Autonomous (LNCS Vol. 3514), 2004.  Proceedings of Asia Simulation Conference, October 2004
Also  published in Springer-Velag Lecture Notes in Computer Science, Vol. 3514 PDF BiBTeX  

2003 Min Hong, Anis Kairmpour-fard, Steve Russell, and Lawrence Hunter. “Integrated Term Weighting, Visualization, and User Interface Development for Bioinformation Retrieval”, The first Rocky Mountain Regional Bioinformatics Meeting, 2003 PDF BiBTeX

 

  

Project description: Since life and the development of all organisms are essentially determined by molecular interactions, the fundamental biological, physical, and chemical understanding of these unsolved detail behaviors of molecules are highly crucial. With the rapid accumulation of 3D structures of proteins, predicting the motion of protein complexes is becoming of increasing interest. These structural data provide many insights on protein folding, protein-ligand interaction, protein-protein interaction and aid more rational approaches to assist drug development and the treatment of diseases. The analysis of deformation of proteins is essential in establishing structure-function relationship because a structure actually carries out a specific function by movement. Although we are using the current state-of-the-art computing power, still it is not computationally possible to perform reliable atomic molecular dynamics simulation for huge protein structures due to the large conformation space. Instead of expensive and complicated force calculations at each time step to achieve the detail deformation of protein, we applied the simple mass-spring system to achieve fast performance and globally reasonable and biologically meaningful deformation of protein structures.

Publications:

Min Hong, David Osguthorpe, and Min-Hyung Choi, Protein Simulation using Fast Volume Preservation, In Proceedings of International Conference on Computational Science Bioimformatics, June 2006 PDF BiBTeX