| 研究領域 | 社会変革の源泉となる革新的アルゴリズム基盤の創出と体系化 |
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| 研究課題/領域番号 |
23H04378
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| 研究種目 |
学術変革領域研究(A)
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| 配分区分 | 補助金 |
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| 審査区分 |
学術変革領域研究区分(Ⅳ)
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| 研究機関 | 山梨大学 |
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研究代表者 |
Koeppl Dominik 山梨大学, 大学院総合研究部, 特任准教授 (50897395)
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| 研究期間 (年度) |
2023-04-01 – 2026-03-31
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| 研究課題ステータス |
交付 (2024年度)
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| 配分額 *注記 |
5,200千円 (直接経費: 4,000千円、間接経費: 1,200千円)
2024年度: 2,600千円 (直接経費: 2,000千円、間接経費: 600千円)
2023年度: 2,600千円 (直接経費: 2,000千円、間接経費: 600千円)
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| キーワード | text indexing / data compression / pattern matching / index construction / string algorithm / resource constraints / matching statistics / compressed indexes / positional BWT / LZ78 factorization / Wheeler DFAs / compressed indices / construction algorithms / r-index / compression algorithms / lossless compression |
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| 研究開始時の研究の概要 |
Major breakthroughs in sequencing techniques facilitate the collection of large amounts of biological data. For these to be of value, we need means to store and analyze them. Here, compressed indices are prospective candidates for answering biologically meaningful queries while keeping the data in a maintainably-small compressed format. Nonetheless, even the construction of those indices is not well studied. In this project, we want to shed light on efficient ways in how to construct such indices and how to use them for the aforementioned queries.
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| 研究実績の概要 |
During fiscal year 2023, we worked on variations of the Burrows-Wheeler transform, one built on a grammar, the positional one, and the Wheeler graph.
Firstly, by storing additionally to the FM-index the index of our DCC'22 paper, we made use of both to accelerate counting queries for all pattern lengths at the expense of more space compared to the FM-index. While the FM-index matches a pattern character-wise, we can switch to the DCC'22-version matching blocks of characters of the pattern defined by the grammar.
Second, we proposed space-efficient data structures that augment the positional Burrows-Wheeler transform for efficiently finding set-maximal exact matches, and compare these with the baseline approach, which uses the plain divergence array.
Thirdly, we worked on matching statistics on Wheeler DFAs, which allows us to match a pattern with multiple reference genome represented by a de-Brujin graph efficiently. Known results use a plain longest common prefix array, which takes space linear to the number of states. We proposed a space-efficient representation that requires a linear number in bits with logarithmic access time. We also give matching statistics computation as an application, which we now can do with a time-space trade-off.
As a side-result, we worked on the substring compression problem for derivates of the LZ78 factorization, which seem to be practically relevant. Here, we used the suffix tree as an index to quickly compute an LZ78-kind factorization of a queried substring range quickly.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
We conducted the research for the fiscal year 2023 as planned,
and can continue with the research for the fiscal year 2024 as highlighted in the research plan.
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| 今後の研究の推進方策 |
We continue our investigation in processing and managing vast amounts of data arising in bioinformatics, thanks to the proliferation of low-cost sequencing technology. Having established some theoretical background for compression techniques during the previous fiscal year, and introduced practical applications of the positional Burrows-Wheeler transform within the realm of bioinformatics, we are now delving deeper into the findings we shared at DCC'24 and exploring variations of our problem settings. Our primary focus remains on constructing indexes utilizing the Burrows-Wheeler transform and data compression techniques within compressed spaces. Our main target is the efficient indexing of the data in bioinformatics, which aligns with the goals of our research project. In particular, we are striving towards publishing our WABI'23 paper in a journal, which introduced an FM-index capable of faster pattern matching by incorporating insights from our DCC'22 paper. In this endeavor, we are replacing grammar compression with prefix-free parsing (PFP). Presently, our implementation relies on a plain Burrows-Wheeler transform (BWT), resulting in a larger memory footprint compared to a standard FM-index, albeit with quicker query times. Switching to run-length compression and fine-tuning the parameters of PFP should lead to significant improvements in memory utilization. Additionally, we are expanding upon our findings from DCC'24 concerning the computation of LZ78 derivatives from suffix trees to compressed indexes.
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