日時 2023年2月7日（火）午後1~2時
場所 東京大学理学部1号館２階 285号室（NSSOL Learning Studio）
場所座標 35.713823964814125, 139.76364458721548 （Googleに入力してください）
BLAST、全ゲノムショットガンアセンブリ、Celera社でのヒトゲノムアセンブリの研究開発で知られ、アルゴリズム分野では suffix array, string graph, chaining 等のパイオニア研究をされた Gene Myers 先生が来日されるのを機会に、ご講演をお願いしました。内容は
● 先生が最近取り組まれている記号列の融合のための効率的アルゴリズム
● ゲノム科学で今後重要になってくる問題
です。
コロナ感染対策のため座席間に十分な間隔を設ける必要があるため、参加を希望される方は下記のサイトでの事前登録をお願いします。
https://forms.gle/HvV84ouV7f2gT2s17
講義室の広さの都合で、最大65名に達した段階で締め切らさせていただきます。
どうぞよろしくお願いいたします。
東京大学 森下真一 鈴木慶彦
A 2-Part Seminar
Gene Myers
Adjunct Faculty, Okinawa Institute of Science and Technology
Emeritus Director, Max Planck Institute for Molecular Cell Biology and Genetics
Merging Sorted Lists of Similar Strings (20min)
Merging T sorted, non-redundant lists containing M elements into a single sorted, non-redundant result of size N ≥ M/T is a classic problem typically solved practically in O(M log T) time with a priority-queue data structure the most basic of which is the simple heap. We revisit this problem in the situation where the list elements are strings and the lists contain many identical or nearly identical elements. By keeping auxiliary information with each heap node, we devise an O(M log T + S) worst-case method that performs no more character comparisons than the sum of the lengths of all the strings S, and another O(M log(T/e) + S) method that becomes progressively more efficient as a function of the fraction of equal elements e = M/N between input lists, reaching linear time when the lists are all identical. The methods perform favorably in practice versus an alternate formulation based on a trie.
High Fidelity Genome Sequencing: What have we been missing? (40min)
This talk will start with a short history of the sequencing of genomes from Sanger to the haplotype-phased, chromosome level reconstructions that are the current state of the art today. Then several examples will be given of biologically meaningful features that would not previously have been seen in previous unphased reconstructions. The talk ends with a summary of future directions and problems that have yet to be solved.
