MUDDIS
Contents
Research Project
MUDDIS, Multidimensional Semantic Integration Approach for Knowledge Discovery
Project Summary
MUDDIS is a collaboration project with National institute of health. The driving principle in using multi-dimensional approach is to create effective domain specific knowledge discovery, based on gene annotation with the use of scientific and provenance information from different resources. Find the similarity between genes can be useful in different areas of life science and biomedical fields such as model organism research and drug discovery in human. We regroup genes based on their functional annotations, structural annotations, genes responsible for disorders and gene-drug interactions. The novelty of this work is to query through different data sources and make a collection of data for similarity calculation calculated in different levels of granularity. Data from literature, open public databases such as OMIM and gene-centered information at NCBI are used as individual resources for different feature of the gene. Each additional features increases the value of knowledge that can be explained within individual resources.
To illustrate the utility of MUDDIS, we designed an evaluation frame work and discussed the correlation between score of MUDDIS similarity and score from structural similarity such as HomoloGene ot compared with curated similarity data such as GMI. The significant finding is candidates for knowledge discovery and allow domain experts to identify, produce and verify new hypotheses.
Contribution
- Data integration for finding the similarity between genes for knowledge discovery.
- Describing different features for gene annotation.
- Extracting data from different data sets from structural to unstructured data sets.
- Providing a systematic approach for finding the similarity between genes from term-term similarity to set-set, feature-feature and finally gene-gene similarity based on semantic similarity.
- Providing a comprehensive evaluation frame work for this platform.
Use Cases
- Using Ontology for Annotation
Kino-Phylo is an integrated suite of tools that enables scientists to annotate phylogenetic related web-based documents as a branch of Kino(Ranabahu, panahiazar, et al., 2011). Kino-Phylo can annotate documents by accessing PhylOnt and other NCBO ontologies.
Project Period
2012 – Current
Collaborative Partners
Kno.e.sis Center, Wright State University University of Georgia
External Collaborations
University of Maryland, College Park
Publications
Maryam Panahiazar, Ajith, Ranabahu, Vahid Taslimi, Hima, Yalamanchili, Arlin Stoltzfus, Jim Leebens-Mack, and Amit Sheth. IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012, 52: 1, 106-116 lower than 20% acceptance rate
Maryam Panahiazar, Amit Sheth, Jim Leebens-Mack. To be published in BMC Medical Genomics Special Issue in Feb 2013
