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18 papers · ranked by Valyu relevance

01
PPubMed15 Sep 2004
Bioconductor: open software development for computational biology and bioinformatics
Robert C Gentleman, Vincent J Carey, Douglas M Bates, Ben Bolstad + 21 more
'Marcel Dettling' 'Sandrine Dudoit' 'Byron Ellis' 'Laurent Gautier' 'Yongchao Ge' 'Jeff Gentry' 'Kurt Hornik' 'Torsten Hothorn' 'Wolfgang Huber' 'Stefano Iacus' 'Rafael Irizarry' 'Friedrich Leisch' 'Cheng Li' 'Martin Maechler' 'Anthony J Rossini' 'Gunther Sawitzki' 'Colin Smith' 'Gordon Smyth' 'Luke Tierney' 'Jean YH…
97relevance
02
BbioRxiv27 Mar 2019
Orchestrating Single-Cell Analysis with Bioconductor
Robert A. Amezquita, Vince J. Carey, Lindsay N. Carpp, Ludwig Geistlinger + 12 more
Recent developments in experimental technologies such as single-cell RNA sequencing have enabled the profiling a high-dimensional number of genome-wide features in individual cells, inspiring the formation of large-scale data generation projects quantifying unprecedented levels of biological variation at the…
94relevance
03
PPubMed26 Sep 2008
Advanced Genomic Data Mining
Xosé M. Fernández-Suárez, Ewan Birney, Fran Lewitter
BioConductor is open source software for the analysis of genomic data. It is based on the R language (which is an implementation of the S language, a statistical programming language originally developed at Bell Laboratories to support research and data analysis of large statistical projects ). R is an integrated…
91relevance
04
PPubMed22 Apr 2025
Learning and teaching biological data science in the Bioconductor community
Jenny Drnevich, Frederick J. Tan, Fabricio Almeida-Silva, Robert Castelo + 15 more
'Robert Castelo' 'Aedin C. Culhane' 'Sean Davis' 'Maria A. Doyle' 'Ludwig Geistlinger' 'Andrew R. Ghazi' 'Susan Holmes' 'Leo Lahti' 'Alexandru Mahmoud' 'Kozo Nishida' 'Marcel Ramos' 'Kevin Rue-Albrecht' 'David J. H. Shih' 'Laurent Gatto' 'Charlotte Soneson' 'B.F. Francis Ouellette'] Modern biological research is…
90relevance
05
PPubMed11 Mar 2025
Learning and teaching biological data science in the Bioconductor community
Jenny Drnevich, Frederick J Tan, Fabricio Almeida-Silva, Robert Castelo + 14 more
'Robert Castelo' 'Aedin C Culhane' 'Sean Davis' 'Maria A Doyle' 'Ludwig Geistlinger' 'Andrew R Ghazi' 'Susan Holmes' 'Leo Lahti' 'Alexandru Mahmoud' 'Kozo Nishida' 'Marcel Ramos' 'Kevin Rue-Albrecht' 'David JH Shih' 'Laurent Gatto' 'Charlotte Soneson'] Modern biological research is increasingly data-intensive, leading…
90relevance
06
BbioRxiv19 May 2019
*BiocPkgTools*: Toolkit for Mining the *Bioconductor* Package Ecosystem
Shian Su, Vincent J. Carey, Lori Shepherd, Matthew Ritchie + 2 more
The Bioconductor project, a large collection of open source software for the comprehension of large-scale biological data, continues to grow with new packages added each week, motivating the development of software tools focused on exposing package metadata to developers and users. The resulting BiocPkgTools package…
87relevance
07
BbioRxiv13 Sep 2023
The tidyomics ecosystem: Enhancing omic data analyses
WJ Hutchison, TJ Keyes, LH Crowell, C Soneson + 18 more
The exponential growth of omic data presents challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor offers an extensive data analysis platform and community, while R tidy programming offers a standard data organisation and manipulation that has revolutionised data science.…
85relevance
08
AarXiv2 Oct 2024
Learning and teaching biological data science in the Bioconductor community
Jenny Drnevich, Frederick J. Tan, Fabricio Almeida‐Silva, Robert Castelo + 12 more
community Authors: ['Jenny Drnevich' 'Frederick J. Tan' 'Fabricio Almeida‐Silva' 'Robert Castelo' 'Aedín C. Culhane' 'Sean Davis' 'Maria Doyle' 'Susan Holmes' 'Leo Lahti' 'Alexandru Mahmoud' 'Kozo Nishida' 'Marcel Ramos' 'Kévin Rue-Albrecht' 'David Shih' 'Laurent Gatto' 'Charlotte Soneson'] Jenny Drnevich1, , Frederick…
85relevance
09
AarXiv18 May 2013
Using R and Bioconductor for proteomics data analysis
Laurent Gatto, Andy Christoforou
This review presents how R, the popular statistical environment and programming language, can be used in the frame of proteomics data analysis. A short introduction to R is given, with special emphasis on some of the features that make R and its add-on packages a premium software for sound and reproducible data…
83relevance
10
PPubMed21 Dec 2010
An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators
Laurent Gautier
Background Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer language has relative strong points, making some languages better suited than others for a given task to be…
82relevance
11
BbioRxiv28 Oct 2021
Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor
Kelly B. Eckenrode, Dario Righelli, Marcel Ramos, Ricard Argelaguet + 8 more
The majority of high-throughput single-cell molecular profiling methods quantify RNA expression; however, recent multimodal profiling methods add simultaneous measurement of genomic, proteomic, epigenetic, and/or spatial information on the same cells. The development of new statistical and computational methods in…
80relevance
12
BbioRxiv26 Jul 2018
The R package *Rsubread* is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads
Yang Liao, Gordon K. Smyth, Wei Shi
The first steps in the analysis of RNA sequencing (RNA-seq) data are usually to map the reads to a reference genome and then to count reads by gene, by exon or by exon-exon junction. These two steps are at once the most common and also typically the most expensive computational steps in an RNA-seq analysis. These steps…
78relevance
13
AarXiv2 Dec 2019
RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow
Kuan-Hao Chao, Yi-Wen Hsiao, Yi-Fang Lee, Chien‐Yueh Lee + 4 more
'Liang‐Chuan Lai' 'Mong‐Hsun Tsai' 'Tzu‐Pin Lu' 'Eric Y. Chuang'] Abstract—RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the…
75relevance
14
AarXiv2013
Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor
María Rodrigo-Domingo, Rasmus Waagepetersen, Julie Støve Bødker, Steffen Falgreen + 4 more
'Steffen Falgreen' 'Malene Krag Kjeldsen' 'Hans Erik Johnsen' 'Karen Dybkær' 'Martin Bøgsted'] Alternative splicing is the posttranscriptional process by which a single gene can produce multiple transcripts and thereby protein isoforms. The presence of different transcripts of a gene across samples can be analysed by…
75relevance
15
CchemRxiv9 Jun 2025
xcms at 20 and still in peak form: Anchoring a complete metabolomics data preprocessing and analysis software ecosystem
Authors not listed
High-quality data preprocessing is essential for untargeted metabolomics experiments, where increasing dataset scale and complexity demand adaptable, robust, and reproducible software solutions. Modern preprocessing tools must evolve to integrate seamlessly with downstream analysis platforms, ensuring efficient and…
74relevance
16
CchemRxiv13 Sep 2025
Leveraging R for Advanced Interpretation of LDI-TOF Mass Spectra: A Computational Approach
Authors not listed
Mass spectrometric analysis of inorganic materials is widely used. However, no major advances were made in this area compared to the significant progress in the analysis of biological materials. This work introduces a novel open-source R workflow that efficiently processes and models isotopic distributions in LDI-TOF…
65relevance
17
CchemRxiv3 Oct 2022
LFQ-based peptide and protein intensity downstream analysis
Mingze Bai, Jingwen Deng, Chengxin Dai, Julianus Pfeuffer + 1 more
Testing for significant differences in quantities on protein level is a common goal of many LFQ-based mass spectrometry proteomics experiments. Starting from a table of protein and/or peptide quantities from a fixed proteomics quantification software, there exists a multitude of tools and R packages to perform the…
64relevance
18
CchemRxiv28 Sep 2022
Discovering life’s directed metabolic (sub)paths to interpret biochemical markers using the DSMN
Denise Slenter, M. Kutmon, Chris T. Evelo, Egon L. Willighagen
Metabolomics data analysis for phenotype identification commonly reveals only a small set of biochemical markers, often containing overlapping metabolites for individual phenotypes. Differentiation between distinctive sample groups requires understanding the underlying causes of metabolic changes. However, combining…
51relevance

Results for Bioconductor

Bioconductor: open software development for computational biology and bioinformatics

Orchestrating Single-Cell Analysis with Bioconductor

Advanced Genomic Data Mining

Learning and teaching biological data science in the Bioconductor community

Learning and teaching biological data science in the Bioconductor community

BiocPkgTools: Toolkit for Mining the Bioconductor Package Ecosystem

The tidyomics ecosystem: Enhancing omic data analyses

Learning and teaching biological data science in the Bioconductor community

Using R and Bioconductor for proteomics data analysis

An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor

xcms at 20 and still in peak form: Anchoring a complete metabolomics data preprocessing and analysis software ecosystem

Leveraging R for Advanced Interpretation of LDI-TOF Mass Spectra: A Computational Approach

LFQ-based peptide and protein intensity downstream analysis

Discovering life’s directed metabolic (sub)paths to interpret biochemical markers using the DSMN

Bioconductor: open software development for computational biology and bioinformatics

Orchestrating Single-Cell Analysis with Bioconductor

Advanced Genomic Data Mining

Learning and teaching biological data science in the Bioconductor community

Learning and teaching biological data science in the Bioconductor community

BiocPkgTools: Toolkit for Mining the Bioconductor Package Ecosystem

The tidyomics ecosystem: Enhancing omic data analyses

Learning and teaching biological data science in the Bioconductor community

Using R and Bioconductor for proteomics data analysis

An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor

xcms at 20 and still in peak form: Anchoring a complete metabolomics data preprocessing and analysis software ecosystem

Leveraging R for Advanced Interpretation of LDI-TOF Mass Spectra: A Computational Approach

LFQ-based peptide and protein intensity downstream analysis

Discovering life’s directed metabolic (sub)paths to interpret biochemical markers using the DSMN

Results for Bioconductor

Bioconductor: open software development for computational biology and bioinformatics

Orchestrating Single-Cell Analysis with Bioconductor

Advanced Genomic Data Mining

Learning and teaching biological data science in the Bioconductor community

Learning and teaching biological data science in the Bioconductor community

*BiocPkgTools*: Toolkit for Mining the *Bioconductor* Package Ecosystem

The tidyomics ecosystem: Enhancing omic data analyses

Learning and teaching biological data science in the Bioconductor community

Using R and Bioconductor for proteomics data analysis

An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

The R package *Rsubread* is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor

xcms at 20 and still in peak form: Anchoring a complete metabolomics data preprocessing and analysis software ecosystem

Leveraging R for Advanced Interpretation of LDI-TOF Mass Spectra: A Computational Approach

LFQ-based peptide and protein intensity downstream analysis

Discovering life’s directed metabolic (sub)paths to interpret biochemical markers using the DSMN

Bioconductor: open software development for computational biology and bioinformatics

Orchestrating Single-Cell Analysis with Bioconductor

Advanced Genomic Data Mining

Learning and teaching biological data science in the Bioconductor community

Learning and teaching biological data science in the Bioconductor community

*BiocPkgTools*: Toolkit for Mining the *Bioconductor* Package Ecosystem

The tidyomics ecosystem: Enhancing omic data analyses

Learning and teaching biological data science in the Bioconductor community

Using R and Bioconductor for proteomics data analysis

An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

The R package *Rsubread* is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor

xcms at 20 and still in peak form: Anchoring a complete metabolomics data preprocessing and analysis software ecosystem

Leveraging R for Advanced Interpretation of LDI-TOF Mass Spectra: A Computational Approach

LFQ-based peptide and protein intensity downstream analysis

Discovering life’s directed metabolic (sub)paths to interpret biochemical markers using the DSMN

BiocPkgTools: Toolkit for Mining the Bioconductor Package Ecosystem

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

BiocPkgTools: Toolkit for Mining the Bioconductor Package Ecosystem

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads