[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83060-en":3,"doc-seo-83060-105":30,"detail-sidebar-cat-0-en-105":83},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},83060,1374391975076,"Riley","https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051",8,"Research & Report","Compiling Bioinformatics Recurrences","Compiling Bioinformatics Recurrences introduces FILTR, a domain-specific language and compiler framework for bioinformatics recurrence equations expressed over dynamic programming matrices. FILTR separates core recurrence rules from pruning and scheduling: pruning approximates which DP cells are computed, and scheduling sets the iteration order. The system compiles high-level descriptions into optimized C++ code that matches hand-tuned performance, enabling fast exploration of new heuristics. Benchmarks show FILTR runs 0.95× to 30× faster than hand-optimized sequence-alignment libraries across biological workloads.","arXiv :2607 .06225v 1 [ cs .PL] 7 Jul 2026  \nCompiling Bioinformatics Recurrences  \nBALA VINAITHIRTHAN, Stanford University, USA SHIV SUNDRAM, Stanford University, USASNEHA GOENKA, Princeton University, USA FREDRIK KJOLSTAD, Stanford University, USA  \nMany bioinformatics algorithms, such as sequence alignment and structure prediction, can be expressed as recurrence equations over a dynamic programming matrix. Efficient implementations of these algorithms for large-scale biological data often require changing the order in which matrix cells are calculated and pruning ineffectual regions of the matrix from consideration altogether, but these techniques typically complicate implementation. We introduce FILTR, a domain-specific language (DSL) and compiler framework for bioinformatics recurrences. FILTR keeps the core recurrence rules separate from the pruning and scheduling strategies, where pruning acts as an approximation to limit where in the DP matrix cells are computed, and scheduling determines the iteration order for how cells are explored. FILTR compiles these high-level descriptions into optimized C++ code that matches the performance of hand-tuned implementations while enabling rapid exploration of new heuristics. FILTR is competitive with hand-optimized sequence-alignment libraries, ranging from 0. 95× to 30× faster across biological benchmarks.  \n1 Introduction  \nLiving organisms are built from sequences of recurring sub-components. DNA consists of repeating nucleotides, genes contain recurring sequences, proteins are chains of repeating amino acids, and larger structures like cells and tissues are composed of recurring molecular building blocks [8, 33] . Hence, modeling bioinformatics problems is often reduced to identifying and comparing recurring sequences and structural patterns [51, 60, 64] . Examples include comparing two DNA sequences to see how similar they are, predicting how an RNA folds [39, 46, 71], identifying shared patterns across genes [47, 67], and inferring evolutionary relationships between species [10, 15, 19] .  \nRecurrences decompose sequence modeling problems into overlapping sub-problems. A recurrence equation defines a sequence where each value is calculated in terms of its preceding terms. A classic example from bioinformatics is the Smith–Waterman algorithm [54] that determines local alignment by identifying similar regions between a reference and a query sequence. Another example is the Needleman–Wunsch algorithm [44] that finds the similarity between sequences of comparable length such as complete genes or proteins. Both are ubiquitous in practice and form the crux of critical computational pipelines [20, 26, 27, 29, 31, 40]. Recurrences are typically implemented with dynamic programming (DP). In both Smith–Waterman and Needleman–Wunsch, the core operation is a two-dimensional DP that generates an optimal alignment by computing a matrix of possible edits, in which individual DP cells track the minimum cost of replacing, deleting, or inserting characters to morph, or align, the query string into the reference string.  \nReal-world deployment of bioinformatics sequence algorithms relies on both semantics-preserving performance optimization and non-semantics-preserving algorithmic approximation to scale to millions or, in the case of the human genome, billions of base pairs [43, 45] . Moreover, different application pipelines require different accuracy thresholds—for example, finding a mutation requires the exact differences, while finding the regions onto which subsequences map requires only approximate matching. Since the design space of dynamic programs in bioinformatics is large and varied, bioinformaticians have invested substantial effort in creating optimized variants  \nAuthors’ Contact Information: Bala Vinaithirthan, [balavinaithirthan@stanford.edu](balavinaithirthan@stanford.edu), Stanford University, Stanford, California, USA; Shiv Sundram, [shiv1@stanford.edu](shiv1@stanford.edu), S","cbCaiunV7eetQaMt","https://ap.wps.com/l/cbCaiunV7eetQaMt","pdf",2355693,2,1,28,"English","en",105,"# Introduction\n## Recurrences and dynamic programming in bioinformatics\n## Optimization, approximation, and scalability\n## Motivation for a DSL and compiler","[{\"question\":\"What performance results does the document report for FILTR?\",\"answer\":\"FILTR compiles descriptions into optimized C++ code and is reported to be competitive with hand-tuned sequence-alignment libraries, achieving speedups ranging from 0.95× to 30× across biological benchmarks.\"}]",1784184928,71,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":78,"head_meta":80,"extra_data":82,"updated_unix":28},"compiling-bioinformatics-recurrences","",{"@graph":36,"@context":77},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,47,50],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":20},"https://docshare.wps.com/document/","Document",{"item":48,"name":12,"@type":43,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/compiling-bioinformatics-recurrences/83060/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-21","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71],{"name":72,"@type":73,"acceptedAnswer":74},"What performance results does the document report for FILTR?","Question",{"text":75,"@type":76},"FILTR compiles descriptions into optimized C++ code and is reported to be competitive with hand-tuned sequence-alignment libraries, achieving speedups ranging from 0.95× to 30× across biological benchmarks.","Answer","https://schema.org",{"og:url":51,"og:type":79,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":81,"canonical":51},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":84},[85,89,93,97,102,107,112,115,120,123,127],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":86,"show_sort_weight":87,"slug":88},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":90,"show_sort_weight":91,"slug":92},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Exam",70,"exam",{"id":98,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},5,"Comic",60,"comic",{"id":103,"doc_module":4,"doc_module_name":46,"category_name":104,"show_sort_weight":105,"slug":106},6,"Technology",50,"technology",{"id":108,"doc_module":4,"doc_module_name":46,"category_name":109,"show_sort_weight":110,"slug":111},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":113,"slug":114},30,"research-report",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":98,"slug":130},19,"General","general"]