PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The goal of this study is to test the feasiblity of directly using molecular descriptor data to generate clusters of similar molecules. We have developed an approach that utilizes the "most orthogonal" molecular descriptor variables as a basis set for clustering. In this study we have specifically utilized normal skin tissue and melanoma cancer data derived via Fourier transform infrared (FTIR) spectroscopy to generate these clusters, but the approach presented should be applicable to any other molecular descriptor or response data. Using the three most orthogonal FTIR frequencies as a basis set for cluster analysis, normal skin and melanoma tumors' clusters were resolved and localized in the three-dimensional variable/frequency space. Such clusters can be used to rapidly identify molecules with similar structures, and biological activity given their physico-chemical descriptors or molecular response data. This study also points out possible fallacies when inspecting clusters and how they can be avoided.
Sydney Sukuta
"Utilizing molecular data descriptors as basis vectors for clustering", Proc. SPIE 4966, Microarrays and Combinatorial Technologies for Biomedical Applications: Design, Fabrication, and Analysis, (18 July 2003); https://doi.org/10.1117/12.477783
ACCESS THE FULL ARTICLE
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Sydney Sukuta, "Utilizing molecular data descriptors as basis vectors for clustering," Proc. SPIE 4966, Microarrays and Combinatorial Technologies for Biomedical Applications: Design, Fabrication, and Analysis, (18 July 2003); https://doi.org/10.1117/12.477783