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Genomic signal processing has been used successfully in bioinformatics to analyze biomolecular sequences and gain varied insights into DNA structure, gene organization, protein binding, sequence evolution, etc. But challenges remain in…

Genomics · Quantitative Biology 2022-11-04 Saish Jaiswal , Shreya Nema , Hema A Murthy , Manikandan Narayanan

Summary: Biospectrogam is an open-source software for the spectral analysis of DNA and protein sequences. The software can fetch (from NCBI server), import and manage biological data. One can analyze the data using Digital Signal Processing…

Quantitative Methods · Quantitative Biology 2012-10-05 Naman Turakhia , Nilay Chheda , Manish K. Gupta , Ruchin Shah , Jigar Raisinghani

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

In this paper we describe a new technique for the comparison of populations of DNA strands. Comparison is vital to the study of ecological systems, at both the micro and macro scales. Existing methods make use of DNA sequencing and cloning,…

Biomolecules · Quantitative Biology 2008-07-02 Dennis Shasha , Martyn Amos

Questions of understanding and quantifying the representation and amount of information in organisms have become a central part of biological research, as they potentially hold the key to fundamental advances. In this paper, we demonstrate…

Genomics · Quantitative Biology 2007-10-30 H. M. Aktulga , I. Kontoyiannis , L. A. Lyznik , L. Szpankowski , A. Y. Grama , W. Szpankowski

Gene set analysis, a popular approach for analyzing high-throughput gene expression data, aims to identify sets of related genes that show significantly enriched or depleted expression patterns between different conditions. In the last…

We perform differential expression analysis of high-throughput sequencing count data under a Bayesian nonparametric framework, removing sophisticated ad-hoc pre-processing steps commonly required in existing algorithms. We propose to use…

Applications · Statistics 2017-05-04 Siamak Zamani Dadaneh , Xiaoning Qian , Mingyuan Zhou

High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read count variability. These estimates are…

Background: Significance analysis plays a major role in identifying and ranking genes, transcription factor binding sites, DNA methylation regions, and other high-throughput features for association with disease. We propose a new approach,…

Methodology · Statistics 2017-01-10 Andrew E. Jaffe , John D. Storey , Hongkai Ji , Jeffrey T. Leek

The fall of prices of the high-throughput genome sequencing changes the landscape of modern genomics. A number of large scale projects aimed at sequencing many human genomes are in progress. Genome sequencing also becomes an important aid…

Data Structures and Algorithms · Computer Science 2017-03-03 Sebastian Deorowicz , Agnieszka Danek , Marcin Niemiec

In this study, we explore how quantum pathfinding algorithm called Gaussian Amplitude Amplification (GAA) can be used to solve the DNA sequencing problem. To do this, sequencing by hybridization was assumed wherein short fragments of the…

Mesoscale and Nanoscale Physics · Physics 2023-11-01 Richard Marin , Carlos Baldo

Principal component analysis (PCA) is routinely used in population genetics to assess genetic structure. With chromosomal reference genomes and population-scale whole genome-sequencing becoming increasingly accessible, contemporary studies…

Populations and Evolution · Quantitative Biology 2025-01-22 L. Moritz Blumer , Jeffrey M. Good , Richard Durbin

Haplotype-resolved de novo assembly is the ultimate solution to the study of sequence variations in a genome. However, existing algorithms either collapse heterozygous alleles into one consensus copy or fail to cleanly separate the…

Genomics · Quantitative Biology 2021-02-03 Haoyu Cheng , Gregory T Concepcion , Xiaowen Feng , Haowen Zhang , Heng Li

High-throughput RNA sequencing (RNA-seq) has emerged as a revolutionary and powerful technology for expression profiling. Most proposed methods for detecting differentially expressed (DE) genes from RNA-seq are based on statistics that…

Genomics · Quantitative Biology 2014-11-18 Li Zhang , Xuejun Liu , Songcan Chen

Raw nanopore signal analysis is a common approach in genomics to provide fast and resource-efficient analysis without translating the signals to bases (i.e., without basecalling). However, existing solutions cannot interpret raw signals…

High read depth can be used to assemble short sequence repeats. The existing genome assemblers fail in repetitive regions of longer than average read. I propose a new algorithm for a DNA assembly which uses the relative frequency of reads…

Genomics · Quantitative Biology 2015-01-08 Robert M. Nowak

Bam-readcount is a utility for generating low-level information about sequencing data at specific nucleotide positions. Originally designed to help filter genomic mutation calls, the metrics it outputs are useful as input for variant…

Motivation: The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is…

Genomics · Quantitative Biology 2024-05-30 Heng Li , Maximillian Marin , Maha Reda Farhat

DNA sequencing is the process of determining the exact order of the nucleotide bases of an individual's genome in order to catalogue sequence variation and understand its biological implications. Whole-genome sequencing techniques produce…

Data Structures and Algorithms · Computer Science 2015-09-18 Ljiljana Brankovic , Costas S. Iliopoulos , Ritu Kundu , Manal Mohamed , Solon P. Pissis , Fatima Vayani

Summary: BWA-MEM is a new alignment algorithm for aligning sequence reads or long query sequences against a large reference genome such as human. It automatically chooses between local and end-to-end alignments, supports paired-end reads…

Genomics · Quantitative Biology 2013-05-28 Heng Li