PANI : an interactive data-driven tool for target prioritization in signaling networks
Biological network analysis often aims at the target identification problem, which is to predict which molecule to inhibit (or activate) for a disease treatment to achieve optimum efficacy and safety. A related goal, arising from the increasing availability of high-throughput screening (HTS), is to...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/107227 http://hdl.handle.net/10220/16672 |
| _version_ | 1811686292693450752 |
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| author | Bhowmick, Sourav S. Chua, Huey-Eng Tucker-Kellogg, Lisa Wang, Yingqi Dewey Jr., C. Forbes Yu, Hanry |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Bhowmick, Sourav S. Chua, Huey-Eng Tucker-Kellogg, Lisa Wang, Yingqi Dewey Jr., C. Forbes Yu, Hanry |
| author_sort | Bhowmick, Sourav S. |
| collection | NTU |
| description | Biological network analysis often aims at the target identification problem, which is to predict which molecule to inhibit (or activate) for a disease treatment to achieve optimum efficacy and safety. A related goal, arising from the increasing availability of high-throughput screening (HTS), is to suggest many molecules as potential targets. The target prioritization problem is to predict a subset of molecules in a given disease-associated network which is likely to include successful drug targets. Sensitivity analysis prioritizes targets in a dynamic network model according to principled criteria, but fails to penalize off-target effects, and does not scale for large networks. In this demonstration, we present PANI(Putative TArget Nodes PrIoritization), a novel interactive system that addresses these limitations. It prunes and ranks the possible target nodes by exploiting concentration-time profiles and network structure (topological) information and visually display them in the context of the signaling network. Through the interactive user interface, we demonstrate various innovative features of PANI that enhance users' understanding of the prioritized nodes. |
| first_indexed | 2024-10-01T04:58:06Z |
| format | Conference Paper |
| id | ntu-10356/107227 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:58:06Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1072272020-05-28T07:18:27Z PANI : an interactive data-driven tool for target prioritization in signaling networks Bhowmick, Sourav S. Chua, Huey-Eng Tucker-Kellogg, Lisa Wang, Yingqi Dewey Jr., C. Forbes Yu, Hanry School of Computer Engineering International Health Informatics Symposium (2nd : 2012 : Miami, USA) DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Biological network analysis often aims at the target identification problem, which is to predict which molecule to inhibit (or activate) for a disease treatment to achieve optimum efficacy and safety. A related goal, arising from the increasing availability of high-throughput screening (HTS), is to suggest many molecules as potential targets. The target prioritization problem is to predict a subset of molecules in a given disease-associated network which is likely to include successful drug targets. Sensitivity analysis prioritizes targets in a dynamic network model according to principled criteria, but fails to penalize off-target effects, and does not scale for large networks. In this demonstration, we present PANI(Putative TArget Nodes PrIoritization), a novel interactive system that addresses these limitations. It prunes and ranks the possible target nodes by exploiting concentration-time profiles and network structure (topological) information and visually display them in the context of the signaling network. Through the interactive user interface, we demonstrate various innovative features of PANI that enhance users' understanding of the prioritized nodes. 2013-10-21T09:12:01Z 2019-12-06T22:27:05Z 2013-10-21T09:12:01Z 2019-12-06T22:27:05Z 2012 2012 Conference Paper Chua, H.-E., Bhowmick, S. S., Tucker-Kellogg, L., Wang, Y., Dewey, C. F., & Yu, H. (2012). PANI : an interactive data-driven tool for target prioritization in signaling networks. Proceedings of the 2nd ACM SIGHIT symposium on International health informatics-IHI '12, pp851-854. https://hdl.handle.net/10356/107227 http://hdl.handle.net/10220/16672 10.1145/2110363.2110471 en |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Bhowmick, Sourav S. Chua, Huey-Eng Tucker-Kellogg, Lisa Wang, Yingqi Dewey Jr., C. Forbes Yu, Hanry PANI : an interactive data-driven tool for target prioritization in signaling networks |
| title | PANI : an interactive data-driven tool for target prioritization in signaling networks |
| title_full | PANI : an interactive data-driven tool for target prioritization in signaling networks |
| title_fullStr | PANI : an interactive data-driven tool for target prioritization in signaling networks |
| title_full_unstemmed | PANI : an interactive data-driven tool for target prioritization in signaling networks |
| title_short | PANI : an interactive data-driven tool for target prioritization in signaling networks |
| title_sort | pani an interactive data driven tool for target prioritization in signaling networks |
| topic | DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences |
| url | https://hdl.handle.net/10356/107227 http://hdl.handle.net/10220/16672 |
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