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| Αναζήτηση Προφίλ HMMER× | Μεταγονιδιωματική ομαδοποίηση (Metagenomic Binning)× | |
|---|---|---|
| Πεδίο | Βιοπληροφορική | Βιοπληροφορική |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 1994 | 2011 |
| Δημιουργός≠ | Sean Eddy | Jillian Banfield |
| Τύπος≠ | Probabilistic sequence search pipeline | Sequence assembly and clustering pipeline |
| Θεμελιώδης πηγή≠ | 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 ↗ | Kang, D. D., Froula, J., Egan, R., & Wang, Z. (2015). MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ, 3, e1165. DOI ↗ |
| Εναλλακτικές ονομασίες | profile-hidden Markov model, HMM profile search, HMMER | metagenomic assembly, genome binning, MAG recovery |
| Συναφείς | 3 | 3 |
| Σύνοψη≠ | 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. | Metagenomic binning partitions assembled contigs from complex microbial communities into distinct genome bins, each representing an individual organism or strain. Pioneered by Banfield and colleagues, this pipeline isolates single-organism genomes (metagenome-assembled genomes or MAGs) from environmental samples without requiring cultivated isolates. |
| ScholarGateΣύνολο δεδομένων ↗ |
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