So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Lắp ráp transcriptome de novo× | Tìm kiếm Hồ sơ HMMER× | |
|---|---|---|
| Lĩnh vực | Tin sinh học | Tin sinh học |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 2011 | 1994 |
| Người khởi xướng≠ | Aviv Regev | Sean Eddy |
| Loại≠ | Sequence assembly pipeline | Probabilistic sequence search pipeline |
| Công trình gốc≠ | Grabherr, M. G., Haas, B. J., Yassour, M., Levin, J. Z., Thompson, D. A., Amit, I., ... & Regev, A. (2011). Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology, 29(7), 644-652. 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 ↗ |
| Tên gọi khác | transcriptome assembly, de novo assembly, RNA-Seq assembly | profile-hidden Markov model, HMM profile search, HMMER |
| Liên quan | 3 | 3 |
| Tóm tắt≠ | De novo transcriptome assembly reconstructs full-length messenger RNA sequences directly from sequencing reads without requiring a reference genome. Pioneered by Regev, Haas, and colleagues, this pipeline enables transcript discovery in non-model organisms and detection of novel isoforms, fusion genes, and splice variants. | 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. |
| ScholarGateBộ dữ liệu ↗ |
|
|