Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Metagenominen lajittelu× | HMMER-profiilihaku× | |
|---|---|---|
| Tieteenala | Bioinformatiikka | Bioinformatiikka |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 2011 | 1994 |
| Kehittäjä≠ | Jillian Banfield | Sean Eddy |
| Tyyppi≠ | Sequence assembly and clustering pipeline | Probabilistic sequence search pipeline |
| Alkuperäislähde≠ | 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 ↗ | 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 ↗ |
| Rinnakkaisnimet | metagenomic assembly, genome binning, MAG recovery | profile-hidden Markov model, HMM profile search, HMMER |
| Liittyvät | 3 | 3 |
| Tiivistelmä≠ | 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. | 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. |
| ScholarGateAineisto ↗ |
|
|