Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Топология сети белок-белковых взаимодействий× | Поиск по профилю HMMER× | |
|---|---|---|
| Область | Биоинформатика | Биоинформатика |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2000 | 1994 |
| Автор метода≠ | Peter Uetz | Sean Eddy |
| Тип≠ | Network analysis pipeline | Probabilistic sequence search pipeline |
| Основополагающий источник≠ | Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., ... & Lomax, J. (2000). A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature, 403(6770), 623-627. DOI ↗ | Krogh, A., Brown, M., Mian, I. S., Sjölander, K., & Haussler, D. (1994). Hidden Markov models in computational biology: applications to protein modeling. Journal of Molecular Biology, 235(5), 1501-1531. DOI ↗ |
| Другие названия | protein interaction networks, interactome analysis, network topology | profile-hidden Markov model, HMM profile search, HMMER |
| Связанные | 3 | 3 |
| Сводка≠ | Protein-protein interaction network analysis identifies and characterizes the structural properties of cellular interaction networks. Pioneered by Uetz and colleagues through large-scale yeast two-hybrid screening, this approach reveals topological features like hubs, modules, and motifs that encode functional organization and disease associations. | HMMER profile search identifies distant protein sequence homologs using probabilistic models of protein families, known as profile Hidden Markov Models (HMMs). Developed by Eddy and colleagues, this method captures sequence variation patterns within protein families and detects homologs with far greater sensitivity than position-weight matrices or pairwise alignment. |
| ScholarGateНабор данных ↗ |
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