Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Пошук за профілями HMMER× | Метагеномне бінінґування× | |
|---|---|---|
| Галузь | Біоінформатика | Біоінформатика |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1994 | 2011 |
| Автор методу≠ | Sean Eddy | Jillian Banfield |
| Тип≠ | Probabilistic sequence search pipeline | Sequence assembly and clustering pipeline |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | profile-hidden Markov model, HMM profile search, HMMER | metagenomic assembly, genome binning, MAG recovery |
| Пов'язані | 3 | 3 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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