\u7b2c46\u56de\u30a4\u30f3\u30b7\u30ea\u30b3\u30fb\u30e1\u30ac\u30d0\u30f3\u30af\u7814\u7a76\u4f1a\u3092\u4e0b\u8a18\u306e\u3068\u304a\u308a\u884c\u3044\u307e\u3059\u306e\u3067\u3054\u6848\u5185\u3044\u305f\u3057\u307e\u3059\u3002<\/p>\n
\u4eca\u56de\u306f\u7523\u696d\u6280\u8853\u7dcf\u5408\u7814\u7a76\u6240 \u751f\u547d\u60c5\u5831\u5de5\u5b66\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u30fbMartin Frith\u5148\u751f\u3092\u8b1b\u5e2b\u3068\u3057\u3066\u304a\u8fce\u3048\u3057\u3001\u300c\u5143\u6765\u306e\u7d71\u8a08\u7684\u30a2\u30e9\u30a4\u30e1\u30f3\u30c8\u306b\u304a\u3051\u308b\u6700\u65b0\u9ad8\u30b9\u30eb\u30fc\u30d7\u30c3\u30c8DNA\u306e\u9069\u5fdc\u300d\u306b\u3064\u3044\u3066\u8b1b\u6f14\u3057\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002<\/p>\n
\u30fb\u65e5\u6642\uff1a\u5e73\u621026\u5e742\u670821\u65e5(\u91d1)\u300017\uff1a00\u201018\uff1a30 \uff0a\u672c\u8b1b\u6f14\u306f\u533b\u5b66\u7cfb\u7814\u7a76\u79d1\u7cfb\u7d71\u8b1b\u7fa9\u30b3\u30fc\u30b9\u79d1\u76ee\u306e\u6388\u696d\u3068\u3057\u3066\u632f\u66ff\u53ef\u80fd\u3067\u3059\u3002<\/p>\n For many decades, the main way of analyzing biological sequences has been by comparing and aligning them.\u00a0 This remains true today.\u00a0 Modern tasks include: comparing whole genomes; aligning bisulfite-converted DNA reads to a genome; aligning long, high-error sequences from single molecule sequencers; aligning ancient or degraded DNA; comparing metagenomic DNA to a protein database. Over the decades, statistically powerful alignment techniques have been developed, including: log likelihood ratio scoring matrices, pair hidden Markov models, and probabilistic alignment.\u00a0 Unfortunately, these methods are rarely used with modern deep sequencing data, This talk will also sketch how to incorporate some new features into classic statistical alignment: sequence quality data (phred scores); pairing relationships between DNA reads; and split alignment, where different parts of one query sequence may align to disjoint loci in a genome.\u00a0 This is useful for genome rearrangements, spliced RNA splicing), and even whole genome comparison.\u00a0 The statistical approach can tell us the reliability (unambiguity) of any part of an alignment.<\/p>\n \u30fb\u4e16\u8a71\u4eba: \u9577\ufa11\u6b63\u6717<\/p>\n","protected":false},"excerpt":{"rendered":" \u7b2c46\u56de\u30a4\u30f3\u30b7\u30ea\u30b3\u30fb\u30e1\u30ac\u30d0\u30f3\u30af\u7814\u7a76\u4f1a\u3092\u4e0b\u8a18\u306e\u3068\u304a\u308a\u884c\u3044\u307e\u3059\u306e\u3067\u3054\u6848\u5185\u3044\u305f\u3057\u307e\u3059\u3002 … \u7d9a\u304d\u3092\u8aad\u3080
\n\u30fb\u5834\u6240\uff1a\u6771\u5317\u30e1\u30c7\u30a3\u30ab\u30eb\u30fb\u30e1\u30ac\u30d0\u30f3\u30af\u6a5f\u69cb2\u968e\u4f1a\u8b70\u5ba41<\/a>
\n\u30fb\u6f14\u984c\uff1aAdapting classic statistical alignment to modern high-throughput DNA
\n\u30fb\u8b1b\u5e2b\uff1aMartin Frith\uff08\u7523\u696d\u6280\u8853\u7dcf\u5408\u7814\u7a76\u6240 \u751f\u547d\u60c5\u5831\u5de5\u5b66\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\uff09<\/p>\n