AbstractMotivation. Estimating mutation rates between evolutionarily related sequences is a central problem in molecular evolution. Due to the rapid expans

Randomness is a powerful tool in the design and analysis of algorithms and data structures for nucleotide sequence data. Nucleotide sequences are not themselves random but are often randomized using hash functions. Despite their widespread use in genomics, there is no comprehensive review of the types of hash functions used and their various applications. In this survey intended for bioinformatic methods developers, we divide hash functions into four categories: scattering hash functions, permutations, minimum perfect hash functions, and locality-sensitive hash functions. For each category, we provide examples of both general-use hash functions that have been applied in nucleotide sequence analysis and hash functions that have been designed specifically for nucleotide sequence analysis. We highlight their salient properties, commonalities, differences, and application areas.

Matematiska institutionen består av cirka 120 forskare, lärare och administrativ personal och är organiserad i tre huvudsakliga avdelningar: Matematik, Matematisk statistik och Beräkningsmatematik

An easy-to-use, flexible website template for labs, with automatic citations, GitHub tag imports, pre-built components, and more.

Probabilistic membership filters support fast approximate membership queries with a controlled false-positive probability $\varepsilon$ and are widely used across storage, analytics, networking, and b...

Workshop Data Structures in Bioinformatics

The Azrieli Fellows Program is an elite group of academics who cultivate a network of leading professionals in Israel and around the world.

MetaGraph enables scalable indexing of large sets of DNA, RNA or protein sequences using annotated de Bruijn graphs.

Job Description Summary Organization's Summary Statement: The postdoctoral research associate is responsible for developing novel computational methodology for high-throughput sequence genomics tasks,...

Videos on : (a) the Burrows-Wheeler Transform (BWT), (b) the FM Index, which uses the BWT to construct a full-text index, (c) Wheeler graphs, (d) r-index, an...

We introduce Mapping-friendly Sequence Reduction (MSR) sketches, a sketching method for high-fidelity (HiFi) long reads, and Alice, an assembler that operates directly on these sketches. MSR produces ...

Abstract Summary In this article, we introduce the Conway–Bromage–Lyndon (CBL) structure, a compressed, dynamic and exact method for representing k-mer sets. Originating from Conway and Bromage’s concept, CBL innovatively employs the smallest cyclic rotations of k-mers, akin to Lyndon words, to leverage lexicographic redundancies. In order to support dynamic operations and set operations, we propose a dynamic bit vector structure that draws a parallel with Elias-Fano’s scheme. This structure is encapsulated in a Rust library, demonstrating a balanced blend of construction efficiency, cache locality, and compression. Our findings suggest that CBL outperforms existing dynamic k-mer set methods. Unique to this work, CBL stands out as the only known exact k-mer structure offering in-place set operations. Its different combined abilities position it as a flexible Swiss knife structure for k-mer set management. Availability and implementation https://github.com/imartayan/CBL.