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Whole-genome sequencing (WGS) has revealed numerous non-coding short variants whose functional impacts remain poorly understood. Despite recent advances in deep-learning genomic approaches, accurately predicting and prioritizing clinically…

We consider models for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low rates of recall. If some variables can be identified with near certainty, then they can be…

Computer Vision and Pattern Recognition · Computer Science 2009-07-03 Andrew Kae , Gary B. Huang , Erik Learned-Miller

Several biological problems require the identification of regions in a sequence where some feature occurs within a target density range: examples including the location of GC-rich regions, identification of CpG islands, and sequence…

Data Structures and Algorithms · Computer Science 2013-08-15 Benjamin A. Burton , Mathias Hiron

In real-time trajectory planning for unmanned vehicles, on-board sensors, radars and other instruments are used to collect information on possible obstacles to be avoided and pathways to be followed. Since, in practice, observations of the…

Methodology · Statistics 2013-09-25 Adriano Zanin Zambom , Julian A. A. Collazos , Ronaldo Dias

Second-generation sequencing technologies have replaced array-based technologies and become the default method for genomics and epigenomics analysis. Second-generation sequencing technologies sequence tens of millions of DNA/cDNA fragments…

Methodology · Statistics 2017-02-08 Ping Ma , Nan Zhang , Jianhua Z. Huang , Wenxuan Zhong

High throughput sequencing is a technology that allows for the generation of millions of reads of genomic data regarding a study of interest, and data from high throughput sequencing platforms are usually count compositions. Subsequent…

Quantitative Methods · Quantitative Biology 2017-04-07 Jia R. Wu , Jean M. Macklaim , Briana L. Genge , Gregory B. Gloor

Many methods for machine learning rely on approximate inference from intractable probability distributions. Variational inference approximates such distributions by tractable models that can be subsequently used for approximate inference.…

Machine Learning · Computer Science 2020-10-08 Oleg Arenz , Mingjun Zhong , Gerhard Neumann

This article studies the achievable guarantees on the error rates of certain learning algorithms, with particular focus on refining logarithmic factors. Many of the results are based on a general technique for obtaining bounds on the error…

Machine Learning · Computer Science 2016-09-13 Steve Hanneke

Described are two algorithms to find long approximate palindromes in a string, for example a DNA sequence. A simple algorithm requires O(n)-space and almost always runs in $O(k.n)$-time where n is the length of the string and k is the…

Data Structures and Algorithms · Computer Science 2007-05-23 L. Allison

In the last decade a number of algorithms and associated software have been developed to align next generation sequencing (NGS) reads with relevant reference genomes. The accuracy of these programs may vary significantly, especially when…

High-throughput biological assays such as microarrays let us ask very detailed questions about how diseases operate, and promise to let us personalize therapy. Data processing, however, is often not described well enough to allow for exact…

Applications · Statistics 2010-10-07 Keith A. Baggerly , Kevin R. Coombes

Statistical inference on the cancer-site specificities of collective ultra-rare whole genome somatic mutations is an open problem. Traditional statistical methods cannot handle whole-genome mutation data due to their…

Methodology · Statistics 2023-01-02 Saptarshi Chakraborty , Zoe Guan , Colin B. Begg , Ronglai Shen

The application of machine learning models can be significantly impeded by the occurrence of distributional shifts, as the assumption of homogeneity between the population of training and testing samples in machine learning and statistics…

Machine Learning · Statistics 2023-06-06 Wenlu Tang , Zicheng Liu

Variant calling is a fundamental task in genomic research, essential for detecting genetic variations such as single nucleotide polymorphisms (SNPs) and insertions or deletions (indels). This paper presents an enhancement to DeepChem, a…

Quantitative Methods · Quantitative Biology 2025-07-29 Ankita Vaishnobi Bisoi , Shreyas V , Jose Siguenza , Bharath Ramsundar

We present a novel Bayesian approach to analysing multiple time-series with the aim of detecting abnormal regions. These are regions where the properties of the data change from some normal or baseline behaviour. We allow for the…

Applications · Statistics 2015-08-17 Lawrence Bardwell , Paul Fearnhead

RNA sequencing (RNA-seq) is the conventional genome-scale approach used to capture the expression levels of all detectable genes in a biological sample. This is now regularly used for population-based studies designed to identify genetic…

Genomics · Quantitative Biology 2026-05-25 Christopher Thron , Farhad Jafari

The tremdendous advances in high-throughput sequencing technologies have made population-scale sequencing as performed in the 1000 Genomes project and the Genome of the Netherlands project possible. Next-generation sequencing has allowed…

Genomics · Quantitative Biology 2013-03-15 Tobias Marschall , Alexander Schönhuth

Several processes in the cell, such as gene regulation, start when key proteins recognise and bind to short DNA sequences. However, as these sequences can be hundreds of million times shorter than the genome, they are hard to find by simple…

Subcellular Processes · Quantitative Biology 2021-01-27 Markus Nyberg , Tobias Ambjörnsson , Per Stenberg , and Ludvig Lizana

Meta-analyses of diagnostic test accuracy (DTA) studies have been gathering attention in research in clinical epidemiology and health technology development, and bivariate random-effects model is becoming a standard tool. However, standard…

Methodology · Statistics 2020-06-19 Tsubasa Ito , Shonosuke Sugasawa

Genome sequencing is the basis for many modern biological and medicinal studies. With recent technological advances, metagenomics has become a problem of interest. This problem entails the analysis and reconstruction of multiple DNA…

Probability · Mathematics 2022-01-14 Marlee Herring