방법 비교

	HMMER 프로파일 검색	메타게놈 비닝
분야	생물정보학	생물정보학
계열	Process / pipeline	Process / pipeline
기원 연도	1994	2011
창시자	Sean Eddy	Jillian Banfield
유형	Probabilistic sequence search pipeline	Sequence assembly and clustering pipeline
원전	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.	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.
별칭	profile-hidden Markov model, HMM profile search, HMMER	metagenomic assembly, genome binning, MAG recovery
관련	3	3
요약	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.