隐马尔可夫模型（HMM）怎样用于基因预测？
How is a hidden Markov model (HMM) used for gene prediction?
基因组上哪段是“编码区”、哪段是“非编码区”是看不见的隐藏状态，而碱基序列是观测值。HMM 用起始、外显子、内含子、终止等状态及其发射概率，沿着序列找最可能的隐藏状态路径，从而标出基因结构。
Whether a region is coding or non-coding is a hidden state; the base sequence is the observation. An HMM with states like start, exon, intron, stop and their emission probabilities finds the most likely hidden path along the sequence, marking gene structure.
难度 专业 · 适合 高中(15-18)
CC BY 4.0 · 已核验 · Verified 2026-11-04 · 2 条独立证据
来源 · Source
Mario Stanke, Oliver Schöffmann, Burkhard Morgenstern, Stephan Waack,《Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources》,BMC Bioinformatics,2006 (DOI: 10.1186/1471-2105-7-62)
Mario Stanke, Oliver Schöffmann, Burkhard Morgenstern, Stephan Waack, 'Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources', BMC Bioinformatics, 2006, DOI: 10.1186/1471-2105-7-62
独立核验依据 · Independent verification: 核验依据 1 OpenAlex W1487554690 (DOI 10.1186/1471-2105-7-62) · 核验依据 2 CROSSREF 标识 10.1186/1471-2105-7-62：Gene prediction in eu
#HMM #基因
序列比对工具（如 BLAST）在生物学里到底在“找”什么？
What is a sequence-alignment tool like BLAST actually looking for?
它把你的一段 DNA 或蛋白质序列，去和海量已知序列库比较，找出相似度最高的片段。相似往往意味着同源或功能相近，于是能推测未知基因可能干什么、属于哪类生物。
It compares your DNA or protein sequence against huge known databases to find the most similar stretches. Similarity often implies shared origin or function, helping guess what an unknown gene does or which organism it belongs to.
难度 进阶 · 适合 初中(12-15)
CC BY 4.0 · 已核验 · Verified 2026-08-23 · 2 条独立证据
来源 · Source
Cormen, Leiserson, Rivest, Stein,《Introduction to Algorithms》第3版,MIT Press,2009
T. H. Cormen et al., Introduction to Algorithms, 3rd ed., MIT Press, 2009
独立核验依据 · Independent verification: 核验依据 2 ISBN 978-0-262-04630-5
#序列比对 #生物信息
电脑是怎么帮忙“读懂”DNA 的？
How does a computer help 'read' DNA?
DNA 是一长串由 A、T、C、G 四个字母组成的密码。实验仪器先把它们读成文字，电脑再用比对、统计等算法找出哪段像基因、和哪种生物相似，相当于用搜索引擎去翻一本极其庞大的生命字典。
DNA is a long code of four letters A, T, C, G. Machines read it into text, and computers use alignment and statistics to spot which parts look like genes or match other organisms—like searching a vast book of life.
难度 入门 · 适合 小学低段(6-8)
CC BY 4.0 · 来源待核验 · Source pending review
来源 · Source
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Nature (2020) 578:297-301，生物信息算法方法综述
Nature (2020) 578:297-301, review on bioinformatics algorithms and methods
#DNA #生物信息