Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Búsqueda de Perfiles HMMER× | Agrupación Metagenómica× | |
|---|---|---|
| Campo | Bioinformática | Bioinformática |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1994 | 2011 |
| Autor original≠ | Sean Eddy | Jillian Banfield |
| Tipo≠ | Probabilistic sequence search pipeline | Sequence assembly and clustering pipeline |
| Fuente seminal≠ | 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 ↗ |
| Alias | profile-hidden Markov model, HMM profile search, HMMER | metagenomic assembly, genome binning, MAG recovery |
| Relacionados | 3 | 3 |
| Resumen≠ | 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. |
| ScholarGateConjunto de datos ↗ |
|
|