ReviewPLoS computational biology2012
Computational and statistical analysis of protein mass spectrometry data.
Review in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- From bench to bedside via bytes: Multi-omic immunoprofiling and integration using machine learning and network approaches.Human vaccines & immunotherapeutics · 2023Review
- Challenges and Opportunities for Single-cell Computational Proteomics.Molecular & cellular proteomics : MCP · 2023Review
- Discovery of plasma proteome markers associated with clinical outcome and immunological stress after cardiac surgery.Frontiers in cardiovascular medicine · 2023Article
- PeptideShaker Online: A User-Friendly Web-Based Framework for the Identification of Mass Spectrometry-Based Proteomics Data.Journal of proteome research · 2021Article
- Identifying Candidate Biomarkers of Ionizing Radiation in Human Pulmonary Microvascular Lumens Using Microfluidics-A Pilot Study.Micromachines · 2021Article
- Accurate Estimation of Context-Dependent False Discovery Rates in Top-Down Proteomics.Molecular & cellular proteomics : MCP · 2019Article
- A Markov Chain Monte Carlo Method for Estimating the Statistical Significance of Proteoform Identifications by Top-Down Mass Spectrometry.Journal of proteome research · 2019Article
- Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli.Nature communications · 2016Article
- Diagnostic 'omics' for active tuberculosis.BMC medicine · 2016Review
- Mass spectrometry-based protein identification with accurate statistical significance assignment.Bioinformatics (Oxford, England) · 2015Article
- Pathway and network analysis in proteomics.Journal of theoretical biology · 2014Review
- JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy.Molecular & cellular proteomics : MCP · 2014Article
- MS-GF+ makes progress towards a universal database search tool for proteomics.Nature communications · 2014Article
- Multi-TGDR, a multi-class regularization method, identifies the metabolic profiles of hepatocellular carcinoma and cirrhosis infected with hepatitis B or hepatitis C virus.BMC bioinformatics · 2014Article
- Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry.Mass spectrometry (Tokyo, Japan) · 2014Article
- OMICtools: an informative directory for multi-omic data analysis.Database : the journal of biological databases and curation · 2014Article
- Protein analysis by shotgun/bottom-up proteomics.Chemical reviews · 2013Review
- Computational biomarker pipeline from discovery to clinical implementation: plasma proteomic biomarkers for cardiac transplantation.PLoS computational biology · 2013Article
- Determining the calibration of confidence estimation procedures for unique peptides in shotgun proteomics.Journal of proteomics · 2013Article
- Proteomics: from single molecules to biological pathways.Cardiovascular research · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
High-throughput proteomics experiments involving tandem mass spectrometry produce large volumes of complex data that require sophisticated computational analyses. As such, the field offers many challenges for computational biologists. In this article, we briefly introduce some of the core computational and statistical problems in the field and then describe a variety of outstanding problems that readers of PLoS Computational Biology might be able to help solve.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.