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Harald Barsness bilde

Harald Barsnes

Førsteamanuensis
  • E-postHarald.Barsnes@uib.no
  • Telefon+47 55 58 66 65
  • Besøksadresse
    Jonas Lies vei 91
  • Postadresse
    Postboks 7804
    5020 Bergen

Harald Barsnes er gruppeleder ved både proteomikkenheten i Bergen (PROBE)Institutt for biomedisin og ved Computational Biology Unit (CBU)Institutt for informatikk.

Hovedfokuset for gruppens forskning er utvikling av brukervennlige og fritt tilgjengelige bioinformatikkløsninger som lar forskere selv analysere og dele sine egne forskningsdata. For mer informasjon om gruppen se www.cbu.uib.no/barsnes.

Barsnes har sin PhD fra Institutt for informatikk ved Universitetet i Bergen i 2010, med et fokus på bioinformatikk og proteomikk. Etter PhD'en jobbet han ved PROBE ved Institutt for biomedisin, først som senioringeniør og deretter som postdoc finansiert via NFR. Etterfulgt av en periode som forsker ved Klinisk institutt 2 tilknyttet Helge Ræder sin gruppe, før han i 2016 startet sin egen forskningsgruppe finansiert av Bergen forskningsstiftelse og Norges forskningsråd.

Forskningen har resultert i en rekke publikasjoner og en lang liste med fritt tilgjengelig programvare, for eksempel PeptideShakerSearchGUI og PRIDE Converter.

Barsnes har også vært gjesteredaktør i tidsskriftet PROTEOMICS og har vært medforfatter på en lærebok i proteomikk: Computational and Statistical Methods for Protein Quantification by Mass Spectrometry.

I 2015 mottok han Meltzerprisen for unge forskere ved Universitet i Bergen, og i 2016 ble han tildelt rekrutteringsstipend fra Bergen forskningsstiftelse.

Vitenskapelig artikkel
  • Vis forfatter(e) 2021. Cuprizone and EAE mouse frontal cortex proteomics revealed proteins altered in multiple sclerosis. Scientific Reports.
  • Vis forfatter(e) 2020. Leptin receptor signaling regulates protein synthesis pathways and neuronal differentiation in pluripotent stem cells. Stem Cell Reports. 1067-1079.
  • Vis forfatter(e) 2020. Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis. Clinical Proteomics. 1-21.
  • Vis forfatter(e) 2020. Connecting MetaProteomeAnalyzer and PeptideShaker to Unipept for Seamless End-to-End Metaproteomics Data Analysis. Journal of Proteome Research. 3562-3566.
  • Vis forfatter(e) 2019. ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion. Journal of Proteome Research. 537-542.
  • Vis forfatter(e) 2019. Proteomics Standards Initiative Extended FASTA Format. Journal of Proteome Research. 2686-2692.
  • Vis forfatter(e) 2019. PathwayMatcher: proteoform-centric network construction enables fine-granularity multi-omics pathway mapping. GigaScience. 1-13.
  • Vis forfatter(e) 2019. Dynamic proteome profiling of human pluripotent stem cell-derived pancreatic progenitors. Stem Cells. 542-555.
  • Vis forfatter(e) 2019. Detecting single amino acids and small peptides by combining isobaric tags and peptidomics. European Journal of Mass Spectrometry.
  • Vis forfatter(e) 2018. SearchGUI: a highly adaptable common interface for proteomics search and de novo engines. Journal of Proteome Research. 2552-2555.
  • Vis forfatter(e) 2018. Analyzing the Structure of Pathways and Its Influence on the Interpretation of Biomedical Proteomics Data Sets. Journal of Proteome Research. 3801-3809.
  • Vis forfatter(e) 2017. The mzIdentML data standard version 1.2, supporting advances in proteome informatics. Molecular & Cellular Proteomics. 1275-1285.
  • Vis forfatter(e) 2017. PeptideMapper: Efficient and versatile amino acid sequence and tag mapping. Bioinformatics. 2042-2044.
  • Vis forfatter(e) 2017. OLS Client and OLS Dialog: Open source tools to annotate public omics datasets. Proteomics.
  • Vis forfatter(e) 2017. In-depth cerebrospinal fluid quantitative proteome and deglycoproteome analysis: presenting a comprehensive picture of pathways and processes affected by multiple sclerosis. Journal of Proteome Research. 179-194.
  • Vis forfatter(e) 2017. BioContainers: An open-source and community-driven framework for software standardization. Bioinformatics.
  • Vis forfatter(e) 2016. Using Proteomics Bioinformatics Tools and Resources in Proteogenomic Studies. Advances in Experimental Medicine and Biology. 65-75.
  • Vis forfatter(e) 2016. Systemic Analysis of Regulated Functional Networks. Methods in molecular biology. 287-310.
  • Vis forfatter(e) 2016. Practical considerations for omics experiments in biomedical sciences. Current Pharmaceutical Biotechnology. 105-114.
  • Vis forfatter(e) 2016. Pladipus enables universal distributed computing in proteomics bioinformatics. Journal of Proteome Research. 707-712.
  • Vis forfatter(e) 2016. Label-free analysis of human cerebrospinal fluid addressing various normalization strategies and revealing protein groups affected by multiple sclerosis. Proteomics. 1154-1165.
  • Vis forfatter(e) 2016. CSF-PR 2.0: an interactive literature guide to quantitative cerebrospinal fluid mass spectrometry data from neurodegenerative disorders. Molecular & Cellular Proteomics. 300-309.
  • Vis forfatter(e) 2016. A pipeline for differential proteomics in unsequenced species. Journal of Proteome Research. 1963-1970.
  • Vis forfatter(e) 2015. Quantitative proteomics suggests decrease in the secretogranin-1 cerebrospinal fluid levels during the disease course of multiple sclerosis. Proteomics. 3361-3369.
  • Vis forfatter(e) 2015. JSparklines: Making tabular proteomics data come alive. Proteomics. 1428-1431.
  • Vis forfatter(e) 2015. Distributed and interactive visual analysis of omics data. Journal of Proteomics. 78-82.
  • Vis forfatter(e) 2014. Shedding light on black boxes in protein identification. Proteomics. 1001-1005.
  • Vis forfatter(e) 2014. In-depth characterization of the cerebrospinal fluid (CSF) proteome displayed through the CSF proteome resource (CSF-PR). Molecular & Cellular Proteomics. 3152-3163.
  • Vis forfatter(e) 2014. Distributed computing and data storage in proteomics: many hands make light work, and a stronger memory. Proteomics. 367-377.
  • Vis forfatter(e) 2014. DeNovoGUI: an open source graphical user interface for de novo sequencing of tandem mass spectra. Journal of Proteome Research. 1143-1146.
  • Vis forfatter(e) 2014. Carboxyl-ester lipase maturity-onset diabetes of the young disease protein biomarkers in secretin-stimulated duodenal juice. Journal of Proteome Research. 521-530.
  • Vis forfatter(e) 2013. Discovery and initial verification of differentially abundant proteins between multiple sclerosis patients and controls using iTRAQ and SID-SRM. Journal of Proteomics. 312-325.
  • Vis forfatter(e) 2012. Use of stable isotope dimethyl labeling coupled to selected reaction monitoring to enhance throughput by multiplexing relative quantitation of targeted proteins. Analytical Chemistry. 4999-5006.
  • Vis forfatter(e) 2012. The PRoteomics IDEntification (PRIDE) Converter 2 Framework: An Improved Suite of Tools to Facilitate Data Submission to the PRIDE Database and the ProteomeXchange Consortium. Molecular & Cellular Proteomics. 1682-1689.
  • Vis forfatter(e) 2011. thermo-msf-parser: An Open Source Java Library to Parse and Visualize Thermo Proteome Discoverer msf Files. Journal of Proteome Research. 3840-3843.
  • Vis forfatter(e) 2011. compomics-utilities: an open-source Java library for computational proteomics. BMC Bioinformatics. 5 sider.
  • Vis forfatter(e) 2011. Submitting proteomics data to PRIDE using PRIDE Converter. Methods in molecular biology. 237-253.
  • Vis forfatter(e) 2011. SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches. Proteomics. 996-999.
  • Vis forfatter(e) 2011. IsobariQ: Software for Isobaric Quantitative Proteomics using IPTL, iTRAQ, and TMT. Journal of Proteome Research. 913-920.
  • Vis forfatter(e) 2011. A global analysis of peptide fragmentation variability. Proteomics. 1181-1188.
  • Vis forfatter(e) 2010. ms_lims, a simple yet powerful open source LIMS for mass spectrometry-driven proteomics. Proteomics. 1261-1264.
  • Vis forfatter(e) 2010. XTandem Parser: An open-source library to parse and analyse X!Tandem MS/MS search results. Proteomics. 1522-1524.
  • Vis forfatter(e) 2010. The Proteomics Identifications database: 2010 update. Nucleic Acids Research (NAR). D736-D742.
  • Vis forfatter(e) 2010. The Ontology Lookup Service: bigger and better. Nucleic Acids Research (NAR). W155-W160.
  • Vis forfatter(e) 2010. OLS Dialog: An open-source front end to the Ontology Lookup Service. BMC Bioinformatics.
  • Vis forfatter(e) 2010. Fragmentation Analyzer: An open-source tool to analyze MS/MS fragmentation data. Proteomics. 1087-1090.
  • Vis forfatter(e) 2009. Proteomics data collection - 4th ProDaC workshop 15 August 2008, Amsterdam, The Netherlands. Proteomics. 218-222.
  • Vis forfatter(e) 2009. Proteomics Data Collection - 5th ProDaC Workshop: 4 March 2009, Kolympari, Crete, Greece. Proteomics. 3626-3629.
  • Vis forfatter(e) 2009. OMSSA Parser: an open-source library to parse and extract data from OMSSA MS/MS search results. Proteomics. 3772-3774.
  • Vis forfatter(e) 2009. Getting a grip on proteomics data - Proteomics Data Collection (ProDaC). Proteomics. 3928-3933.
  • Vis forfatter(e) 2008. Protease-dependent fractional mass and peptide properties. European Journal of Mass Spectrometry. 311-317.
  • Vis forfatter(e) 2008. Blind search for post-translational modifications and amino acid substitutions using peptide mass fingerprints from two proteases. BMC Research Notes.
  • Vis forfatter(e) 2006. MassSorter: a tool for administrating and analyzing data from mass spectrometry experiments on proteins with known amino acid sequences. BMC Bioinformatics. 9 sider.
Leserinnlegg
  • Vis forfatter(e) 2009. PRIDE Converter: making proteomics data-sharing easy. Nature Biotechnology. 598-599.
Short communication
  • Vis forfatter(e) 2017. An accessible proteogenomics informatics resource for cancer researchers. Cancer Research. e43-e46.
  • Vis forfatter(e) 2013. Pride-asap: automatic fragment ion annotation of identified PRIDE spectra. Journal of Proteomics. 89-92.
Vitenskapelig monografi
  • Vis forfatter(e) 2013. Computational and Statistical Methods for Protein Quantification by Mass Spectrometry.
Brev til redaktøren
  • Vis forfatter(e) 2015. PeptideShaker enables reanalysis of MS-derived proteomics data sets. Nature Biotechnology. 22-24.
Doktorgradsavhandling
  • Vis forfatter(e) 2016. Proteome and deglycopeptide analyses of neurologically healthy and multiple sclerosis affected cerebrospinal fluid: Mass spectrometry experiments, literature mining and data sharing .
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
  • Vis forfatter(e) 2019. Essential Features and Use Cases of the Cerebrospinal Fluid Proteome Resource (CSF-PR). 15 sider.
  • Vis forfatter(e) 2016. Visualization, Inspection and Interpretation of Shotgun Proteomics Identification Results. 10 sider.
  • Vis forfatter(e) 2016. Tandem Mass Spectrum Sequencing: An Alternative to Database Search Engines in Shotgun Proteomics. 10 sider.
  • Vis forfatter(e) 2016. Interpretation of Quantitative Shotgun Proteomic Data. 14 sider.
  • Vis forfatter(e) 2016. Database Search Engines: Paradigms, Challenges and Solutions. 10 sider.
  • Vis forfatter(e) 2016. A Simple Workflow for Large Scale Shotgun Glycoproteomics. 12 sider.
  • Vis forfatter(e) 2014. Bioinformatics for Proteomics: Opportunities at the interface between the scientists, their experiments and the community. 10 sider.
  • Vis forfatter(e) 2008. MassSorter: Peptide Mass Fingerprinting Data Analysis. 15 sider.
Poster
  • Vis forfatter(e) 2011. IsobariQ: Software for isobaric quantitative proteomics using IPTL, iTRAQ and TMT.
Vitenskapelig oversiktsartikkel/review
  • Vis forfatter(e) 2021. Importance of Block Randomization When Designing Proteomics Experiments. Journal of Proteome Research. 122-128.
  • Vis forfatter(e) 2017. Anatomy and evolution of database search engines—a central component of mass spectrometry based proteomic workflows. Mass spectrometry reviews (Print). 292-306.
  • Vis forfatter(e) 2016. Exploring the potential of public proteomics data. Proteomics. 214-225.
  • Vis forfatter(e) 2015. Viewing the proteome: How to visualize proteomics data? Proteomics. 1341-1355.
  • Vis forfatter(e) 2014. Machine learning applications in proteomics research: How the past can boost the future. Proteomics. 353-366.
  • Vis forfatter(e) 2013. Crowdsourcing in proteomics: public resources lead to better experiments. Amino Acids. 1129-1137.

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