Probability Association | Association probability of each genes with age related disorders |
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Amino Acid Composition | Fraction of each amino acid type within a protein. |
Hydrophobicity | The hydrophobicity index is a measure of the relative hydrophobicity, or how soluble an amino acid is in water. Amino acids were classified into 3 categories : Polar, Neutral and hydrophobicity. |
Normalized van der waals volume | Amino acids were categorized into 3 on the basis of their normalized van der waal volume. |
Polarity | The polarity of amino acids has been divided into 3 categories on the basis of their polarity value. |
Charge | According to charge on amino acids were divided into three categories : Positive, negative and neutral. |
Secondary structure | Number of amino acids forming various protein secondary structures : Helix, Strand and Coil. |
Solvent accessibility | It defines the surface of protein which is accessible to water contact. They were classified into three categories : Buried, Exposed and Intermediate. |
Polarizability | It is the ability for a amino acid to be polarized. It is divided into three categories : 0-1.08, 0.128 - 0.186, 0.219-0.409 |
Subcellular Localization | This provides spatial information on protein expression patterns on a fine cellular and subcellular level. |
Betweenness centrality | Betweenness centrality is an indicator of a Protein's centrality in a network. It is equal to the number of shortest paths from all vertices to all others that pass through that protein. |
Closeness centrality | It is measure of how long it will take to spread information from a protein to all other proteins. |
Degree | In the study of network, the degree of a protein in a network is the number of connections it has to other proteins. |
Clustering Coefficient | It is a measure of the degree to which proteins in a network tend to cluster together |
1. | Goh, K., Cusick, ME., Valle. D., Childs, B., Vidal, M., Barabasi, AL., (2007) The human disease network. Proceedings of the National Academy of Sciences, 104:8685. | |
2. | Chaefer, MH., Fontaine, JF., Vinayagam, A., Porras, P., Wanker, EE., Andrade Navarro, MA. (2012) HIPPIE: Integrating Protein Interaction Networks with Experiment Based Quality Scores. Andrade-Navarromail, DOI: 10.1371/journal.pone.0031826. | |
3. | Cline, MS., Smoot, M., Cerami, E., Kuchinsky, A., Landys, N., Workman, C., Christmas, R., Avila Campilo, I., Creech, M., Gross, B., Hanspers, K., Isserlin, R., Kelley, R., Killcoyne, S., Lotia, S., Maere, S., Morris, J., Ono, K., Pavlovic, V., Pico, AR., Vailaya, A., Wang, PL., Adler, A., Conklin, BR., Hood, L., Kuiper, M., Sander, C., Schmulevich, I., Schwikowski, B., Warner, GJ., Ideker, T., Bader, GD. (2007) Integration of biological networks and gene expression data using Cytoscape, Nature Protocols 2, -2366 - 2382, doi:10.1038/nprot.2007.324. | |
4. | Swasti, S., Monika, J. (2013) A Study on WEKA Tool for Data Preprocessing, IJITEE, ISSN: 2278-3075, Volume-2, Issue-6. |