{"entity": "researcher", "timestamp": "2026-07-11T15:09:44.809Z", "family": "Johansson", "given": "Henrik J", "initials": "HJ", "orcid": "0000-0003-4729-4205", "affiliations": [], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a"}}, "publications": [{"entity": "publication", "iuid": "647d53b18b37408db896d3a565fec76c", "links": {"self": {"href": "https://publications.scilifelab.se/publication/647d53b18b37408db896d3a565fec76c.json"}, "display": {"href": "https://publications.scilifelab.se/publication/647d53b18b37408db896d3a565fec76c"}}, "title": "The DNA methylation landscape of primary triple-negative breast cancer.", "authors": [{"family": "Aine", "given": "Mattias", "initials": "M", "orcid": "0000-0002-0851-5952", "researcher": {"href": "https://publications.scilifelab.se/researcher/ec863fc84b064759b355272fa1be61ff.json"}}, {"family": "Nacer", "given": "Deborah F", "initials": "DF", "orcid": "0000-0002-7117-1371", "researcher": {"href": "https://publications.scilifelab.se/researcher/e484e25cfdf64d27842357355409dbfc.json"}}, {"family": "Arbajian", "given": "Elsa", "initials": "E", "orcid": "0000-0002-1484-0073", "researcher": {"href": "https://publications.scilifelab.se/researcher/e9615e08a1a04fada47e805c27a29c61.json"}}, {"family": "Veerla", "given": "Srinivas", "initials": "S", "orcid": "0000-0001-7328-6239", "researcher": {"href": "https://publications.scilifelab.se/researcher/c203a0b3112f4f499ccc79db3e47b303.json"}}, {"family": "Karlsson", "given": "Anna", "initials": "A", "orcid": "0000-0001-6974-5965", "researcher": {"href": "https://publications.scilifelab.se/researcher/016d7daf94304064a461e0df719112c5.json"}}, {"family": "H\u00e4kkinen", "given": "Jari", "initials": "J", "orcid": "0000-0002-8466-9179", "researcher": {"href": "https://publications.scilifelab.se/researcher/9b8605b9a7c74b20986146f020cf4b8f.json"}}, {"family": "Johansson", "given": "Henrik J", "initials": "HJ", "orcid": "0000-0003-4729-4205", "researcher": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a.json"}}, {"family": "Rosengren", "given": "Frida", "initials": "F"}, {"family": "Vallon-Christersson", "given": "Johan", "initials": "J", "orcid": "0000-0002-2195-0385", "researcher": {"href": "https://publications.scilifelab.se/researcher/648fa1d04cb640858fe3534d04cd04d1.json"}}, {"family": "Borg", "given": "\u00c5ke", "initials": "\u00c5", "orcid": "0000-0002-5793-132X", "researcher": {"href": "https://publications.scilifelab.se/researcher/127501d4e0854d14a4120acee9042bb7.json"}}, {"family": "Staaf", "given": "Johan", "initials": "J", "orcid": "0000-0001-5254-5115", "researcher": {"href": "https://publications.scilifelab.se/researcher/07acbd7f211e4809a8195e2ccf5faf57.json"}}], "type": "journal article", "published": "2025-03-28", "journal": {"title": "Nat Commun", "issn": "2041-1723", "volume": "16", "issue": "1", "pages": "3041", "issn-l": "2041-1723"}, "abstract": "Triple-negative breast cancer (TNBC) is a clinically challenging and molecularly heterogenous breast cancer subgroup. Here, we investigate the DNA methylation landscape of TNBC. By analyzing tumor methylome profiles and accounting for the genomic context of CpG methylation, we divide TNBC into two epigenetic subtypes corresponding to a Basal and a non-Basal group, in which characteristic transcriptional patterns are correlated with DNA methylation of distal regulatory elements and epigenetic regulation of key steroid response genes and developmental transcription factors. Further subdivision of the Basal and non-Basal subtypes identifies subgroups transcending genetic and proposed TNBC mRNA subtypes, demonstrating widely differing immunological microenvironments, putative epigenetically-mediated immune evasion strategies, and a specific metabolic gene network in older patients that may be epigenetically regulated. Our study attempts to target the epigenetic backbone of TNBC, an approach that may inform future studies regarding tumor origins and the role of the microenvironment in shaping the cancer epigenome.", "doi": "10.1038/s41467-025-58158-x", "pmid": "40155623", "labels": {"Clinical Genomics Lund": "Service", "NGI Short read": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "National Genomics Infrastructure": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC11953470"}, {"db": "pii", "key": "10.1038/s41467-025-58158-x"}], "notes": [], "created": "2025-04-14T12:30:37.267Z", "modified": "2025-09-08T06:57:25.392Z"}, {"entity": "publication", "iuid": "d4db29d93f3144d29d7dcb207e5ed083", "links": {"self": {"href": "https://publications.scilifelab.se/publication/d4db29d93f3144d29d7dcb207e5ed083.json"}, "display": {"href": "https://publications.scilifelab.se/publication/d4db29d93f3144d29d7dcb207e5ed083"}}, "title": "Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer.", "authors": [{"family": "Wang", "given": "Kang", "initials": "K", "orcid": "0000-0001-5401-1803", "researcher": {"href": "https://publications.scilifelab.se/researcher/7bdb074014224910b0f34e893b15e660.json"}}, {"family": "Zerdes", "given": "Ioannis", "initials": "I", "orcid": "0000-0002-8304-2462", "researcher": {"href": "https://publications.scilifelab.se/researcher/f786763a4a0e4b5bb865ebb199eb6ca2.json"}}, {"family": "Johansson", "given": "Henrik J", "initials": "HJ", "orcid": "0000-0003-4729-4205", "researcher": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a.json"}}, {"family": "Sarhan", "given": "Dhifaf", "initials": "D", "orcid": "0000-0003-0196-4496", "researcher": {"href": "https://publications.scilifelab.se/researcher/22a235fbd46e49ba953ea339b8b8a507.json"}}, {"family": "Sun", "given": "Yizhe", "initials": "Y"}, {"family": "Kanellis", "given": "Dimitris C", "initials": "DC", "orcid": "0000-0001-8690-2010", "researcher": {"href": "https://publications.scilifelab.se/researcher/0921ab7566514fb0a3cd0daf2baabe6e.json"}}, {"family": "Sifakis", "given": "Emmanouil G", "initials": "EG", "orcid": "0000-0001-9919-4471", "researcher": {"href": "https://publications.scilifelab.se/researcher/c8506000a14a4a5286aa557ab67ef690.json"}}, {"family": "Mezheyeuski", "given": "Artur", "initials": "A"}, {"family": "Liu", "given": "Xingrong", "initials": "X"}, {"family": "Loman", "given": "Niklas", "initials": "N"}, {"family": "Hedenfalk", "given": "Ingrid", "initials": "I", "orcid": "0000-0002-6840-3397", "researcher": {"href": "https://publications.scilifelab.se/researcher/c852ed467120466f91d053425077c0b8.json"}}, {"family": "Bergh", "given": "Jonas", "initials": "J", "orcid": "0000-0001-5526-1847", "researcher": {"href": "https://publications.scilifelab.se/researcher/fd38f4f7704144ed9e3f869e197175e6.json"}}, {"family": "Bartek", "given": "Jiri", "initials": "J", "orcid": "0000-0003-2013-7525", "researcher": {"href": "https://publications.scilifelab.se/researcher/cd0d4d98261f41268c76dd91345a1857.json"}}, {"family": "Hatschek", "given": "Thomas", "initials": "T"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Matikas", "given": "Alexios", "initials": "A", "orcid": "0000-0002-4122-9624", "researcher": {"href": "https://publications.scilifelab.se/researcher/0af6483a77d746c2b838414692f1f4ed.json"}}, {"family": "Foukakis", "given": "Theodoros", "initials": "T", "orcid": "0000-0001-8952-9987", "researcher": {"href": "https://publications.scilifelab.se/researcher/7683c0280e9b4145aa54305fb08936a7.json"}}], "type": "journal article", "published": "2024-05-07", "journal": {"title": "Nat Commun", "issn": "2041-1723", "volume": "15", "issue": "1", "pages": "3837", "issn-l": "2041-1723"}, "abstract": "Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.", "doi": "10.1038/s41467-024-47932-y", "pmid": "38714665", "labels": {"Global Proteomics and Proteogenomics": "Collaborative"}, "xrefs": [{"db": "pmc", "key": "PMC11076527"}, {"db": "pii", "key": "10.1038/s41467-024-47932-y"}], "notes": [], "created": "2024-11-27T13:26:50.334Z", "modified": "2024-11-27T13:26:50.959Z"}, {"entity": "publication", "iuid": "e7f90faca0e64cfe9379be8900367d06", "links": {"self": {"href": "https://publications.scilifelab.se/publication/e7f90faca0e64cfe9379be8900367d06.json"}, "display": {"href": "https://publications.scilifelab.se/publication/e7f90faca0e64cfe9379be8900367d06"}}, "title": "Breast cancer quantitative proteome and proteogenomic landscape.", "authors": [{"family": "Johansson", "given": "Henrik J", "initials": "HJ", "orcid": "0000-0003-4729-4205", "researcher": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a.json"}}, {"family": "Socciarelli", "given": "Fabio", "initials": "F"}, {"family": "Vacanti", "given": "Nathaniel M", "initials": "NM"}, {"family": "Haugen", "given": "Mads H", "initials": "MH"}, {"family": "Zhu", "given": "Yafeng", "initials": "Y"}, {"family": "Siavelis", "given": "Ioannis", "initials": "I"}, {"family": "Fernandez-Woodbridge", "given": "Alejandro", "initials": "A"}, {"family": "Aure", "given": "Miriam R", "initials": "MR"}, {"family": "Sennblad", "given": "Bengt", "initials": "B"}, {"family": "Vesterlund", "given": "Mattias", "initials": "M", "orcid": "0000-0001-9471-6592", "researcher": {"href": "https://publications.scilifelab.se/researcher/0942e438993b494db2a3db914852c808.json"}}, {"family": "Branca", "given": "Rui M", "initials": "RM", "orcid": "0000-0003-3890-6476", "researcher": {"href": "https://publications.scilifelab.se/researcher/87d6256540174d3da581d4572f9d182a.json"}}, {"family": "Orre", "given": "Lukas M", "initials": "LM"}, {"family": "Huss", "given": "Mikael", "initials": "M"}, {"family": "Fredlund", "given": "Erik", "initials": "E"}, {"family": "Beraki", "given": "Elsa", "initials": "E"}, {"family": "Garred", "given": "\u00d8ystein", "initials": "\u00d8"}, {"family": "Boekel", "given": "Jorrit", "initials": "J"}, {"family": "Sauer", "given": "Torill", "initials": "T"}, {"family": "Zhao", "given": "Wei", "initials": "W"}, {"family": "Nord", "given": "Silje", "initials": "S"}, {"family": "H\u00f6glander", "given": "Elen K", "initials": "EK"}, {"family": "Jans", "given": "Daniel C", "initials": "DC"}, {"family": "Brismar", "given": "Hjalmar", "initials": "H", "orcid": "0000-0003-0578-4003", "researcher": {"href": "https://publications.scilifelab.se/researcher/1ec23336e2ef4e298f340876f1136dce.json"}}, {"family": "Haukaas", "given": "Tonje H", "initials": "TH"}, {"family": "Bathen", "given": "Tone F", "initials": "TF"}, {"family": "Schlichting", "given": "Ellen", "initials": "E"}, {"family": "Naume", "given": "Bj\u00f8rn", "initials": "B"}, {"family": "Consortia Oslo Breast Cancer Research Consortium (OSBREAC)", "given": "", "initials": ""}, {"family": "Luders", "given": "Torben", "initials": "T"}, {"family": "Borgen", "given": "Elin", "initials": "E"}, {"family": "Kristensen", "given": "Vessela N", "initials": "VN"}, {"family": "Russnes", "given": "Hege G", "initials": "HG"}, {"family": "Lingj\u00e6rde", "given": "Ole Christian", "initials": "OC", "orcid": "0000-0003-3565-4912", "researcher": {"href": "https://publications.scilifelab.se/researcher/759346ec4321470f96ca42af68ed760c.json"}}, {"family": "Mills", "given": "Gordon B", "initials": "GB"}, {"family": "Sahlberg", "given": "Kristine K", "initials": "KK"}, {"family": "B\u00f8rresen-Dale", "given": "Anne-Lise", "initials": "AL"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}], "type": "journal article", "published": "2019-04-08", "journal": {"volume": "10", "issn": "2041-1723", "issue": "1", "pages": "1600", "title": "Nat Commun", "issn-l": "2041-1723"}, "abstract": "In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.", "doi": "10.1038/s41467-019-09018-y", "pmid": "30962452", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Long-term Support WABI": "Collaborative", "Global Proteomics and Proteogenomics": "Technology development", "Integrated Microscopy Technologies Stockholm": "Service", "Bioinformatics Support for Computational Resources": "Service", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1038/s41467-019-09018-y"}, {"db": "pmc", "key": "PMC6453966"}], "notes": [], "created": "2019-04-12T07:18:25.320Z", "modified": "2024-01-16T13:48:44.506Z"}, {"entity": "publication", "iuid": "c5ac8923292c4f80b7f141382febd809", "links": {"self": {"href": "https://publications.scilifelab.se/publication/c5ac8923292c4f80b7f141382febd809.json"}, "display": {"href": "https://publications.scilifelab.se/publication/c5ac8923292c4f80b7f141382febd809"}}, "title": "Heterogeneity and interplay of the extracellular vesicle small RNA transcriptome and proteome.", "authors": [{"family": "Sork", "given": "Helena", "initials": "H", "orcid": "0000-0002-5390-4420", "researcher": {"href": "https://publications.scilifelab.se/researcher/f5d08dad4f2d4ee0a3e3a8f060383da5.json"}}, {"family": "Corso", "given": "Giulia", "initials": "G"}, {"family": "Krjutskov", "given": "Kaarel", "initials": "K"}, {"family": "Johansson", "given": "Henrik J", "initials": "HJ", "orcid": "0000-0003-4729-4205", "researcher": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a.json"}}, {"family": "Nordin", "given": "Joel Z", "initials": "JZ"}, {"family": "Wiklander", "given": "Oscar P B", "initials": "OPB"}, {"family": "Lee", "given": "Yi Xin Fiona", "initials": "YXF", "orcid": "0000-0002-9092-1932", "researcher": {"href": "https://publications.scilifelab.se/researcher/619d8471b5704b45bc8a35ee560b47f7.json"}}, {"family": "Westholm", "given": "Jakub Orzechowski", "initials": "JO", "orcid": "0000-0002-6849-6220", "researcher": {"href": "https://publications.scilifelab.se/researcher/161d8b5fb6734b33ad5f5590edbc0cff.json"}}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Wood", "given": "Matthew J A", "initials": "MJA"}, {"family": "M\u00e4ger", "given": "Imre", "initials": "I"}, {"family": "El Andaloussi", "given": "Samir", "initials": "S"}], "type": "journal article", "published": "2018-07-17", "journal": {"volume": "8", "issn": "2045-2322", "issue": "1", "pages": "10813", "title": "Sci Rep", "issn-l": "2045-2322"}, "abstract": "Extracellular vesicles (EVs) mediate cell-to-cell communication by delivering or displaying macromolecules to their recipient cells. While certain broad-spectrum EV effects reflect their protein cargo composition, others have been attributed to individual EV-loaded molecules such as specific miRNAs. In this work, we have investigated the contents of vesicular cargo using small RNA sequencing of cells and EVs from HEK293T, RD4, C2C12, Neuro2a and C17.2. The majority of RNA content in EVs (49-96%) corresponded to rRNA-, coding- and tRNA fragments, corroborating with our proteomic analysis of HEK293T and C2C12 EVs which showed an enrichment of ribosome and translation-related proteins. On the other hand, the overall proportion of vesicular small RNA was relatively low and variable (2-39%) and mostly comprised of miRNAs and sequences mapping to piRNA loci. Importantly, this is one of the few studies, which systematically links vesicular RNA and protein cargo of vesicles. Our data is particularly useful for future work in unravelling the biological mechanisms underlying vesicular RNA and protein sorting and serves as an important guide in developing EVs as carriers for RNA therapeutics.", "doi": "10.1038/s41598-018-28485-9", "pmid": "30018314", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Long-term Support WABI": "Collaborative", "National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Stockholm (Genomics Production)": "Service", "Global Proteomics and Proteogenomics": "Collaborative", "Bioinformatics Support for Computational Resources": "Service", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1038/s41598-018-28485-9"}, {"db": "pmc", "key": "PMC6050237"}], "notes": [], "created": "2018-08-07T08:38:11.195Z", "modified": "2024-01-16T13:48:45.984Z"}, {"entity": "publication", "iuid": "5c73c68928714d1ca470927905211c8e", "links": {"self": {"href": "https://publications.scilifelab.se/publication/5c73c68928714d1ca470927905211c8e.json"}, "display": {"href": "https://publications.scilifelab.se/publication/5c73c68928714d1ca470927905211c8e"}}, "title": "Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow.", "authors": [{"family": "Zhu", "given": "Yafeng", "initials": "Y"}, {"family": "Orre", "given": "Lukas M", "initials": "LM"}, {"family": "Johansson", "given": "Henrik J", "initials": "HJ", "orcid": "0000-0003-4729-4205", "researcher": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a.json"}}, {"family": "Huss", "given": "Mikael", "initials": "M"}, {"family": "Boekel", "given": "Jorrit", "initials": "J"}, {"family": "Vesterlund", "given": "Mattias", "initials": "M", "orcid": "0000-0001-9471-6592", "researcher": {"href": "https://publications.scilifelab.se/researcher/0942e438993b494db2a3db914852c808.json"}}, {"family": "Fernandez-Woodbridge", "given": "Alejandro", "initials": "A"}, {"family": "Branca", "given": "Rui M M", "initials": "RMM"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}], "type": "journal article", "published": "2018-03-02", "journal": {"volume": "9", "issn": "2041-1723", "issue": "1", "pages": "903", "title": "Nat Commun", "issn-l": "2041-1723"}, "abstract": "Proteogenomics enable the discovery of novel peptides (from unannotated genomic protein-coding loci) and single amino acid variant peptides (derived from single-nucleotide polymorphisms and mutations). Increasing the reliability of these identifications is crucial to ensure their usefulness for genome annotation and potential application as neoantigens in cancer immunotherapy. We here present integrated proteogenomics analysis workflow (IPAW), which combines peptide discovery, curation, and validation. IPAW includes the SpectrumAI tool for automated inspection of MS/MS spectra, eliminating false identifications of single-residue substitution peptides. We employ IPAW to analyze two proteomics data sets acquired from A431 cells and five normal human tissues using extended (pH range, 3-10) high-resolution isoelectric focusing (HiRIEF) pre-fractionation and TMT-based peptide quantitation. The IPAW results provide evidence for the translation of pseudogenes, lncRNAs, short ORFs, alternative ORFs, N-terminal extensions, and intronic sequences. Moreover, our quantitative analysis indicates that protein production from certain pseudogenes and lncRNAs is tissue specific.", "doi": "10.1038/s41467-018-03311-y", "pmid": "29500430", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Long-term Support WABI": "Collaborative", "Bioinformatics Support and Infrastructure": "Collaborative", "Global Proteomics and Proteogenomics": "Technology development", "Bioinformatics Support for Computational Resources": "Service", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1038/s41467-018-03311-y"}, {"db": "pmc", "key": "PMC5834625"}], "notes": [], "created": "2018-03-04T17:55:08.112Z", "modified": "2024-01-16T13:48:46.793Z"}, {"entity": "publication", "iuid": "f5ae0bcb00e84e21ab0bdf4d81044a0c", "links": {"self": {"href": "https://publications.scilifelab.se/publication/f5ae0bcb00e84e21ab0bdf4d81044a0c.json"}, "display": {"href": "https://publications.scilifelab.se/publication/f5ae0bcb00e84e21ab0bdf4d81044a0c"}}, "title": "HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics.", "authors": [{"family": "Branca", "given": "Rui M M", "initials": "RM", "orcid": "0000-0003-3890-6476", "researcher": {"href": "https://publications.scilifelab.se/researcher/87d6256540174d3da581d4572f9d182a.json"}}, {"family": "Orre", "given": "Lukas M", "initials": "LM", "orcid": "0000-0002-0384-1003", "researcher": {"href": "https://publications.scilifelab.se/researcher/7b4e49a93b0143db88059c4d1e9fdc59.json"}}, {"family": "Johansson", "given": "Henrik J", "initials": "HJ", "orcid": "0000-0003-4729-4205", "researcher": {"href": "https://publications.scilifelab.se/researcher/18aebf211fa640f48a7c8d860c168e5a.json"}}, {"family": "Granholm", "given": "Viktor", "initials": "V"}, {"family": "Huss", "given": "Mikael", "initials": "M"}, {"family": "P\u00e9rez-Bercoff", "given": "\u00c5sa", "initials": "\u00c5"}, {"family": "Forshed", "given": "Jenny", "initials": "J"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications.scilifelab.se/researcher/9c9f4444f83e43d79c4772a430ca3969.json"}}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}], "type": "journal article", "published": "2014-01-00", "journal": {"title": "Nat. Methods", "issn": "1548-7105", "volume": "11", "issue": "1", "pages": "59-62", "issn-l": "1548-7091"}, "abstract": "We present a liquid chromatography-mass spectrometry (LC-MS)-based method permitting unbiased (gene prediction-independent) genome-wide discovery of protein-coding loci in higher eukaryotes. Using high-resolution isoelectric focusing (HiRIEF) at the peptide level in the 3.7-5.0 pH range and accurate peptide isoelectric point (pI) prediction, we probed the six-reading-frame translation of the human and mouse genomes and identified 98 and 52 previously undiscovered protein-coding loci, respectively. The method also enabled deep proteome coverage, identifying 13,078 human and 10,637 mouse proteins.", "doi": "10.1038/nmeth.2732", "pmid": "24240322", "labels": {"National Genomics Infrastructure": "Service", "Bioinformatics Support, Infrastructure and Training": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Stockholm (Genomics Production)": "Service", "Bioinformatics Support and Infrastructure": "Service", "Bioinformatics (NBIS)": "Service"}, "xrefs": [{"db": "pii", "key": "nmeth.2732"}], "notes": [], "created": "2023-06-16T12:47:04.864Z", "modified": "2023-06-16T12:47:27.234Z"}]}