Zentrum für Quantitative Biologie

Publikationen des QBiC

Vorabdrucke

  • Cuellar, L. K., Friedrich, A., Gabernet, G., de la Garza, L., Fillinger, S., Seyboldt, A., Oven-Krockhaus, S. zur, Wanke, F., Richter, S., Thaiss, W. M., Horger, M., Malek, N., Harter, K., Bitzer, M., & Nahnsen, S. (2019). Efficient data management infrastructure for the integration of imaging and omics data in life science research. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2019.12.28.889295
  • Ewels, P. A., Peltzer, A., Fillinger, S., Alneberg, J., Patel, H., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2019). nf-core: Community curated bioinformatics pipelines. Cold Spring Harbor Laboratory. https://doi.org/10.1101/610741
  • Harris, N. L., Cock, P. J. A., Fields, C. J., Greshake Tzovaras, B., Heuer, M., Hokamp, K., … Yehudi, Y. (2019). BOSC 2019, the 20th annual Bioinformatics Open Source Conference. F1000Research, 8, 2132. https://doi.org/10.12688/f1000research.21568.1
  • Straub, D., Blackwell, N., Langarica Fuentes, A., Peltzer, A., Nahnsen, S., & Kleindienst, S. (2019). Interpretations of microbial community studies are biased by the selected 16S rRNA gene amplicon sequencing pipeline. https://doi.org/10.1101/2019.12.17.880468

2020

  • Abramov, S. M., Tejada, J., Grimm, L., Schädler, F., Bulaev, A., Tomaszewski, E. J., Byrne, J. M., Straub, D., Thorwarth, H., Amils, R., Kleindienst, S., & Kappler, A. (2020). Role of biogenic Fe(III) minerals as a sink and carrier of heavy metals in the Rio Tinto, Spain. Science of The Total Environment, 718, 137294.
  • Botterweg-Paredes, E., Blaakmeer, A., Hong, S.-Y., Sun, B., Mineri, L., Kruusvee, V., Xie, Y., Straub, D., Ménard, D., Pesquet, E., & Wenkel, S. (2020). Light affects tissue patterning of the hypocotyl in the shade-avoidance response. PLOS Genetics, 16(3), e1008678.
  • Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology.
  • Glodowska, M., Stopelli, E., Schneider, M., Lightfoot, A., Rathi, B., Straub, D., Patzner, M., Duyen, V. T., Berg, M., Kleindienst, S., & Kappler, A. (2020). Role of in Situ Natural Organic Matter in Mobilizing As during Microbial Reduction of FeIII-Mineral-Bearing Aquifer Sediments from Hanoi (Vietnam). Environmental Science & Technology, 54(7), 4149–4159.
  • Kumuthini, J., Chimenti, M., Nahnsen, S., Peltzer, A., Meraba, R., McFadyen, R., Wells, G., Taylor, D., Maienschein-Cline, M., Li, J.-L., Thimmapuram, J., Murthy-Karuturi, R., & Zass, L. (2020). Ten simple rules for providing effective bioinformatics research support. PLOS Computational Biology, 16(3), e1007531.

2019

  1. Benitz, S., Straub, T., Mahajan, U. M., Mutter, J., Czemmel, S., Unruh, T., … Regel, I. (2019). Ring1b-dependent epigenetic remodelling is an essential prerequisite for pancreatic carcinogenesis. Gut, gutjnl-2018-317208.
  2. Bichmann, L., Nelde, A., Ghosh, M., Heumos, L., Mohr, C., Peltzer, A., … Kohlbacher, O. (2019). MHCquant: Automated and Reproducible Data Analysis for Immunopeptidomics. Journal of Proteome Research, 18(11), 3876–3884.
  3. Bilich, T., Nelde, A., Bichmann, L., Roerden, M., Salih, H. R., Kowalewski, … Kohlbacher, O. et al. (2019). The HLA ligandome landscape of chronic myeloid leukemia delineates novel T-cell epitopes for immunotherapy. Blood, 133(6), 550-565.
  4. Blaeschke, F., Paul, M. C., Schuhmann, M. U., Rabsteyn, A., Schroeder, C., Casadei, N., Matthes, J., Mohr, C., … Feuchtinger, T. (2019). Low mutational load in pediatric medulloblastoma still translates into neoantigens as targets for specific T-cell immunotherapy. Cytotherapy.
  5. Bryce, C., Blackwell, N., Straub, D., Kleindienst, S., & Kappler, A. (2019). Draft Genome Sequence of Chlorobium sp. Strain N1, a Marine Fe(II)-Oxidizing Green Sulfur Bacterium. Microbiology Resource Announcements, 8(18).
  6. Cain N., Alka O., Segelke T., Von wuthenau K., Kohlbacher O., Fischer M. (2019) Food fingerprinting: Mass spectrometric determination of the cocoa shell content (Theobroma cacao L.) in cocoa products by HPLC-QTOF-MS. Food Chem.;298:125013.
  7. Eisenmann, B., Czemmel, S., Ziegler, T., Buchholz, G., Kortekamp, A., Trapp, O., … Bogs, J. (2019). Rpv3–1 mediated resistance to grapevine downy mildew is associated with specific host transcriptional responses and the accumulation of stilbenes. BMC Plant Biology, 19(1).
  8. Erlangga, Z., Wolff, K., Poth, T., Peltzer, A., Nahnsen, S., ... Saborowski, M. (2019). Potent Antitumor Activity of Liposomal Irinotecan in an Organoid- and CRISPR-Cas9-Based Murine Model of Gallbladder Cancer. Cancers, 2019, 11(12)
  9. Fillinger, S., de la Garza, L., Peltzer, A., Kohlbacher, O., & Nahnsen, S. (2019). Challenges of big data integration in the life sciences. Analytical and Bioanalytical Chemistry, 411(26), 6791–6800.
  10. Friedrich A., de la Garza L., Kohlbacher O., Nahnsen S. (2019) Interactive Visualization for Large-Scale Multi-factorial Research Designs. In: Auer S., Vidal ME. (eds) Data Integration in the Life Sciences. DILS 2018. Lecture Notes in Computer Science, vol 11371. Springer, Cham
  11. Herster, F., Bittner, Z., Codrea, M. C., Archer, N. K., Heister, M., Löffler, M. W., Heumos, S., … Weber, A. N. R. (2019). Platelets Aggregate With Neutrophils and Promote Skin Pathology in Psoriasis. Frontiers in Immunology, 10.
  12. Kersten E., Dammeier S., Ajana S., Groenewoud J.M.M., Codrea M., et al. (2019) Metabolomics in serum of patients with non-advanced age-related macular degeneration reveals aberrations in the glutamine pathway. PLOS ONE 14(6): e0218457.
  13. Löffler, M. W., Mohr, C., Bichmann, L., Freudenmann, L. K., Walzer, M., … Rammensee, H.-G. (2019). Multi-omics discovery of exome-derived neoantigens in hepatocellular carcinoma. Genome Medicine, 11(1).
  14. Miess, H., Arlt, P., Apel, A. K., Weber, T., Nieselt, K., Hanssen, F., … Gross, H. (2019). The Draft Whole-Genome Sequence of the Antibiotic Producer Empedobacter haloabium ATCC 31962 Provides Indications for Its Taxonomic Reclassification. Microbiology Resource Announcements, 8(45).
  15. Rajaraman, S., Canjuga, D., Ghosh, M., Codrea, M. C., Sieger, R., Wedekink, F., Tatagiba, M., Koch, M., Lauer, U. M., Nahnsen, S., Rammensee, H. G., Mühlebach, M. D., Stevanovic, S., … Tabatabai, G. (2019). Measles Virus-Based Treatments Trigger a Pro-inflammatory Cascade and a Distinctive Immunopeptidome in Glioblastoma. Molecular therapy oncolytics, 12, 147-161
  16. Richardson, J. R., Armbruster, N. S., Günter, M., Biljecki, M., Klenk, J., Heumos, S., & Autenrieth, S. E. (2019). PSM Peptides From Community-Associated Methicillin-Resistant Staphylococcus aureus Impair the Adaptive Immune Response via Modulation of Dendritic Cell Subsets in vivo. Frontiers in Immunology, 10
  17. Schneider, L., Kehl, T., Thedinga, K., Grammes, N. L., Backes, C., Mohr, C., … Lenhof, H.-P. (2019). ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification. Bioinformatics.

2018

  1. Antony, J. S., Latifi, N., Haque, A. K. M. A., Lamsfus-Calle, A., Daniel-Moreno, A., Graeter, S., Baskaran, P., … Kormann, M. S. D. (2018). Gene correction of HBB mutations in CD34+ hematopoietic stem cells using Cas9 mRNA and ssODN donors. Molecular and Cellular Pediatrics, 5(1).
  2. Apweiler, R., Beissbarth, T., Berthold, M. R., Blüthgen, N., Burmeister, Y., ... Kohlbacher, O. et al. (2018) Whither systems medicine? Experimental & Molecular Medicine, 50(3): e453.
  3. Benitz S., Mahajan U. M., Czemmel S., Nahnsen S. et al. (2018). Epigenetic mechanisms drive cellular reprogramming in pancreatic carcinogenesis. Pancreatology, 18(4 Suppl):S92.
  4. D'Alvise P., Böhme F., Codrea M.C., Seitz A., Nahnsen S. (2018). The impact of winter feed type on intestinal microbiota and parasites in honey bees. Apidologie, Springer. 49(2);252–264.
  5. Domingo-Calap, P., Schubert, B., Joly, M., Solis, M., Untrau, M., et al. (2018) An unusually high substitution rate in transplant-associated BK polyomavirus in vivo is further concentrated in HLA-C-bound viral peptides. (M. Vignuzzi, Ed.) PLOS Pathogens, 14(10): e1007368.
  6. Fröhlich, H., Balling, R., Beerenwinkel, N., Kohlbacher, O., Kumar, S., et al. (2018) From hype to reality: data science enabling personalized medicine. BMC Medicine, 16(1).
  7. Kahles, A., Lehmann, K.-V., Toussaint, N. C., Hüser, M., Stark, S. G., et al. (2018) Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients. Cancer Cell, 34(2): 211–224.e6.
  8. Kaur, G., & Pati, P. K. (2018). In silico insights on diverse interacting partners and phosphorylation sites of respiratory burst oxidase homolog (Rbohs) gene families from Arabidopsis and rice. BMC Plant Biology, 18(1)
  9. Korkmaz A.G., Popov T., Peisl L., Codrea M.C., Nahnsen S. (2018). Proteome and phosphoproteome analysis of commensally induced dendritic cell maturation states. Journal of Proteomics, 180:11-24.
  10. Löffler, M. W., Kowalewski, D. J., Backert, L., Bernhardt, J., Adam, P., ... Kohlbacher, O. et al. (2018) Mapping the HLA Ligandome of Colorectal Cancer Reveals an Imprint of Malignant Cell Transformation. Cancer Research, 78(16): 4627–4641.
  11. Mohr, C., Friedrich, A., Wojnar, D., Kenar, E., Polatkan, A. C., Codrea, M. C., Czemmel, S., Kohlbacher, O., and Nahnsen, S. (2018). qPortal: A platform for data-driven biomedical research. PloS one, 13(1), e0191603.
  12. Nelde, A., Kowalewski, D. J., Backert, L., Schuster, H., Werner, J.-O., et al. (2018) HLA ligandome analysis of primary chronic lymphocytic leukemia (CLL) cells under lenalidomide treatment confirms the suitability of lenalidomide for combination with T-cell-based immunotherapy. OncoImmunology, 7(4): e1316438.
  13. Schubert, B., Schärfe, C., Dönnes, P., Hopf, T., Marks, D., et al. (2018) Population-specific design of de-immunized protein biotherapeutics. (R. L. Dunbrack, Ed.)PLOS Computational Biology, 14(3): e1005983.
  14. van de Poel, S., Dreer, M., Velic, A., Macek, B., Baskaran, P., et al. (2018) Identification and functional characterization of phosphorylation sites of the HPV31 E8^E2 protein. Journal of Virology, JVI.01743-17.
  15. Walz, J. S., Kowalewski, D. J., Backert, L., Nelde, A., Kohlbacher, O., et al. (2018). Favorable immune signature in CLL patients, defined by antigen-specific T-cell responses, might prevent second skin cancers. Leukemia & Lymphoma, 59(8), 1949–1958.

2017

  1. Armeanu-Ebinger, S., Hadaschik, D., Kyzirakos, C., Mohr, C. et. al (2017). Number of predicted tumour-neoantigens as biomarker for cancer immunotherapies. Annals of Oncology, Vol. 28(suppl_7), 12-12.
  2. Audain et al., (2017). In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics. J Proteomics.;150:170-182.
  3. Backert et al., (2017) A meta-analysis of HLA peptidome composition in different hematological entities: entity-specific dividing lines and "pan-leukemia" antigens. Oncotarget.;8(27):43915-43924.
  4. Boyles et al., (2017). Copper oxide nanoparticle toxicity profiling using untargeted metabolomics. Part Fibre Toxicol.;13(1):49.
  5. Chevrette, M. G., Aicheler, F., Kohlbacher, O., Currie, C. R., & Medema, M. H. (2017) SANDPUMA: ensemble predictions of nonribosomal peptide chemistry reveal biosynthetic diversity across Actinobacteria. (I. Birol, Ed.)Bioinformatics, 33(20): 3202–3210.
  6. Czemmel et al., (2017) Transcriptome-Wide Identification of Novel UV-B- and Light Modulated Flavonol Pathway Genes Controlled by VviMYBF1. Front Plant Sci.;8:1084.
  7. Dittmann, K., Mayer, C., Czemmel, S., Huber, S. M., & Rodemann, H. P. (2017). New roles for nuclear EGFR in regulating the stability and translation of mRNAs associated with VEGF signaling. (C. J. Wilusz, Ed.) PLOS ONE, 12(12): e0189087.
  8. Fellows Yates J. A., Drucker D. G., Reiter E., Heumos S., Welker F., Münzel S. C., … Krause J. (2017). Central European Woolly Mammoth Population Dynamics: Insights from Late Pleistocene Mitochondrial Genomes. Scientific Reports, 7(1).
  9. Flett, F. J., Sachsenberg, T., Kohlbacher, O., Mackay, C. L., & Interthal, H. (2017) Differential Enzymatic 16O/18O Labeling for the Detection of Cross-Linked Nucleic Acid–Protein Heteroconjugates. Analytical Chemistry, 89(21): 11208–11213.
  10. Löffler, M. W., Chandran, P. A., Laske, K., Schroeder, C., Bonzheim, I., ... Mohr, C., ... , Kohlbacher, O. et al. (2017) Erratum to “Personalized peptide vaccine-induced immune response associated with long-term survival of a metastatic cholangiocarcinoma patient.” Journal of Hepatology, 66(1): 252–253.
  11. Schärfe, C. P. I., Tremmel, R., Schwab, M., Kohlbacher, O., & Marks, D. S. (2017) Genetic variation in human drug-related genes. Genome Medicine, 9(1).
  12. Schubert et al., (2017) ImmunoNodes - graphical development of complex immunoinformatics workflows. BMC Bioinformatics.;18(1):242.
  13. Schuster, H., Peper, J. K., Bösmüller, H.-C., Röhle, K., Backert, L., ... Kohlbacher, O. et al. (2017) The immunopeptidomic landscape of ovarian carcinomas. Proceedings of the National Academy of Sciences, 114(46): E9942–E9951.
  14. Vizcaíno et al., (2017). A community proposal to integrate proteomics activities in ELIXIR. F1000Res.;6. pii: ELIXIR-875.
  15. Vizcaíno et al., (2017). The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics. Mol Cell Proteomics.;16(7):1275-1285.

2016

  1. Breckels et al., (2016). Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics. PLoS Comput Biol.;12(5):e1004920.
  2. Codrea MC, Nahnsen S (2016). Platforms and Pipelines for Proteomics Data Analysis and Management. Adv Exp Med Biol.;919:203-215. Review.
  3. Dammeier et al., (2016). Mass-Spectrometry-Based Proteomics Reveals Organ-Specific Expression Patterns To Be Used as Forensic Evidence. J Proteome Res.;15(1):182-92.
  4. Gatto et al., (2016). Testing and Validation of Computational Methods for Mass Spectrometry. J Proteome Res.;15(3):809-14.
  5. Griss et al., (2016). Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets. Nat Methods.;13(8):651-656. Epub 2016 Jun 27.
  6. Hesselager et al., (2016). The Pig PeptideAtlas: A resource for systems biology in animal production and biomedicine. Proteomics.;16(4):634-44.
  7. Hong, H. S., Koch, S. D., Scheel, B., Gnad-Vogt, U., Schröder, A.,  Kallen, K.J., Wiegand, V., Backert, L., Kohlbacher, O. et al. (2016) Distinct transcriptional changes in non-small cell lung cancer patients associated with multi-antigenic RNActive® CV9201 immunotherapy. OncoImmunology, 5(12): e1249560.
  8. Kohlbacher et al., (2016). Challenges in Large-Scale Computational Mass Spectrometry and Multiomics. J Proteome Res.;15(3):681-2.
  9. Kowalewski et al., (2016). Carfilzomib alters the HLA-presented peptidome of myeloma cells and impairs presentation of peptides with aromatic C-termini. Blood Cancer J.;6:e411.
  10. Kyzirakos, C., Mohr, C. et. al (2016). Optimized neoantigen selection based on tumor exome data. Annals of Oncology, 27(suppl_6).
  11. Löffler et al., (2016). Personalized peptide vaccine-induced immune response associated with long-term survival of a metastatic cholangiocarcinoma patient. J Hepatol.;66(1):252-253.
  12. Loyola R et al., (2016). The photomorphogenic factors UV-B RECEPTOR 1, ELONGATED HYPOCOTYL 5, and HY5 HOMOLOGUE are part of the UV-B signalling pathway in grapevine and mediate flavonol accumulation in response to the environment. J Exp Bot.;67(18):5429-5445.
  13. Mueller et al., (2016) BALL-SNPgp-from genetic variants toward computational diagnostics. Bioinformatics.;32(12):1888-90.
  14. Rabsteyn, A., Kyzirakos, C., Schröder, C., Sturm, M., Mohr, C. et. al (2016). Abstract A113: iVacALL: A personalized peptide-vaccination design platform for pediatric acute lymphoblastic leukemia patients based on patient- individual tumor-specific variants. Cancer Immunology Research, 4(1 Supplement), A113.
  15. Ranninger et al., (2016). Improving global feature detectabilities through scan range splitting for untargeted metabolomics by high-performance liquid chromatography-Orbitrap mass spectrometry. Anal Chim Acta.;930:13-22.
  16. Röst et al., (2016) OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Methods.;13(9):741-8.
  17. Schubert et al., (2016). FRED 2: an immunoinformatics framework for Python. Bioinformatics.;32(13):2044-6.
  18. Schubert B, Kohlbacher O. (2016). Designing string-of-beads vaccines with optimal spacers. Genome Med.;8(1):9.
  19. Sinnberg T et al., (2016) A Nexus Consisting of Beta-Catenin and Stat3 Attenuates BRAF Inhibitor Efficacy and Mediates Acquired Resistance to Vemurafenib. EBioMedicine.;8:132-149.
  20. Veit et al., (2016). LFQProfiler and RNP(xl): Open-Source Tools for Label-Free Quantification and Protein-RNA Cross-Linking Integrated into Proteome Discoverer. J Proteome Res.;15(9):3441-8.

2015

  1. Aicheler, F, Li, J, Lehmann, R, Xu, G, and Kohlbacher, O, (2015), Retention Time Prediction Improves Identification in Non-Targeted Lipidomics Approaches. Anal Chem. 87(15):7698-704.
  2. Backert, L., & Kohlbacher, O. (2015). Immunoinformatics and epitope prediction in the age of genomic medicine. Genome Medicine, 7(1).
  3. Engel, B. D., Schaffer, M., Kuhn Cuellar, L., Villa, E., Plitzko, J. M., & Baumeister, W. (2015). Native architecture of the Chlamydomonas chloroplast revealed by in situ cryo-electron tomography. eLife, 4(4), 1–29.
  4. Friedrich, A, Kenar, E, Kohlbacher, O, and Nahnsen, S, (2015), Intuitive Web-based Experimental Design for High-throughput Biomedical Data. BioMed Res Int, 2015:958302.
  5. Hesselager, M. O., Codrea, M. C., & Bendixen, E. (2015). Evaluation of preparation methods for MS-based analysis of intestinal epithelial cell proteomes. Proteomics, 15(13), 2350–2357.
  6. Hildebrandt, AK, Stöckel,D, Fischer, N, de la Garza Trevino, L, Krüger, J, Nickels, S, Röttig, M, Schärfe, C, Schumann, M, Thiel, P, Lenhof, HP, Kohlbacher, O, and Hildebrandt, A, (2015), ballaxy: web services for structural bioinformatics. Bioinformatics, 31(1):121-2.
  7. Martens, L, Kohlbacher, O, and Weintraub, ST, (2015), Managing Expectations when Publishing Tools and Methods for Computational Proteomics. J. Proteome Res., 14(5):2002-4.
  8. Proikas-Cezanne, T, Takacs, Z, Dönnes, P, and Kohlbacher, O (2015). WIPI proteins: essential PtdIns3P effectors at the nascent autophagosome, J. Cell Sci., 128 (2):207-217.
  9. Ranninger, C, Rurik, M, Limonciel, A, Ruzek, S, Reischl, R, Wilmes, A, Jennings, P, Hewitt, P, Dekant, W, Kohlbacher, O, and Huber, CG (2015). Nephron Toxicity Profiling via Untargeted Metabolome Analysis Emplying a High-Performance Liquid Chromatography-Mass Spectrometry-Based Experimental and Computational Pipeline, J. Biol. Chem., 290(31):19121-32.
  10. Sachsenberg, T, Herbst, F, Taubert, M, Kermer, R, Jehmlich, N, von Bergen, M, Seifert, J, and Kohlbacher, O (2015). MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics, J. Proteome Res., 14(2):619-27.
  11. Schubert, B, Brachvogel, H, Jürges, C, and Kohlbacher, O (2015). EpiToolKit - A Web-based Workbench for Vaccine Design. Bioinformatics, 31(13):2211-3.
  12. Sharma, K., Hrle, A., Kramer, K., Sachsenberg, T., Staals, R. H. J., Randau, L., … ,  Kohlbacher, O., Conti, E., Urlaub, H. (2015). Analysis of protein–RNA interactions in CRISPR proteins and effector complexes by UV-induced cross-linking and mass spectrometry. Methods, 89, 138-148.
  13. Thost, A, Dönnes, P, Kohlbacher, O, and Proikas-Cezanne, T (2015). Fluorescence-based imaging of autophagy progression by human WIPI beta-propeller protein detection in single cells. Methods, 75:69-78.
  14. Ziller, MJ, Edri, R, Yaffe, Y, Donaghey, J, Pop, R, Mallard, W, Issner, R, Gifford, CA, Goren, A, Xing, J, Gu, H, Cacchiarelli, D, Tsankov, AM, Epstein, C, Rinn, JL, Mikkelsen, TS, Kohlbacher, O, Gnirke, A, Bernstein, BE, Elkabetz, Y, and Meissner, A (2015). Dissecting neural differentiation regulatory networks through epigenetic footprinting. Nature, 518:355-359.

2014

  1. Gerasch, A, Faber, D, Küntzer, J, Niermann, P, Kohlbacher, O, Lenhof, H, and Kaufmann, M (2014). BiNA: a visual analytics tool for biological network data. PLoS ONE, 9(2):e87397.
  2. Gofman, Y., Schärfe, C., Marks, D. S., Haliloglu, T., & Ben-Tal, N. (2014). Structure, Dynamics and Implied Gating Mechanism of a Human Cyclic Nucleotide-Gated Channel. (M. Nilges, Ed.)PLoS Computational Biology, 10(12): e1003976.
  3. Griss, J, et al., (2014). The mzTab Data Exchange Format: communicating MS-based proteomics and metabolomics experimental results to a wider audience. Mol. Cell. Prot.:mcp.O113.036681.
  4. Hildebrandt AK, Stöckel D, Fischer NM, de la Garza L, Krüger J, Nickels S, Röttig M, Schärfe C et al., (2014). ballaxy: web services for structural bioinformatics. 31(1):121-2.
  5. Hopf, TA, et al., (2014). Sequence co-evolution gives 3D contacts and structures of protein complexes. eLife:10.7554/eLife.03430.
  6. Jordan, E, et al., (2014). Competing Salt Effects on Phase Behavior of Protein Solutions: Tailoring of Protein Interaction by the Binding of Multivalent Ions and Charge Screening. J. Phys. Chem. B, 118(38):11365-74.
  7. Kenar, E, Franken, H, Forcisi, S, Wörmann, K, Häring, H, Lehmann, R, Schmitt-Kopplin, P, Zell, A, and Kohlbacher, O (2014). Automated Label-Free Quantification of Metabolites from LC-MS Data. Mol. Cell. Prot., 13(1):348-59.
  8. Kramer, K, et al., (2014), Photo-cross linking and high-resolution mass spectrometry for assignment of RNA-binding sites in RNA-binding proteins. Nat. Methods, 11(10):1064-70.
  9. Krüger, J, Grunzke, R, Herres-Pawlies, S, de la Garza, L, Kohlbacher, O, Nagel, WE, and Gesing, S (2014), Performance Studies on Distributed Virtual Screening. 2014:624024.
  10. Kuhn Cuellar, L., Pfeffer, S., Chen, Y., & Förster, F. (2014). Automated detection of polysomes in cryoelectron tomography. In 2014 IEEE International Conference on Image Processing, ICIP 2014 (pp. 2085–2089). IEEE.
  11. Olabarriaga, S.D., Benabdelkader, A., Caan, M.W., Jaghoori, M.M., Krüger, J., de la Garza, L., Mohr, C. et. al (2014). WS-PGRADE/gUSE- Based Science Gateways in Teaching. In Science Gateways for Distributed Computing Infrastructures, Springer, Cham., 223-234.
  12. Restelli, L., Codrea, M. C., Savoini, G., Ceciliani, F., & Bendixen, E. (2014). LC-MS/MS analysis of visceral and subcutaneous adipose tissue proteomes in young goats with focus on innate immunity and inflammation related proteins. Journal of Proteomics, 108, 295–305.
  13. Szolek, A., Schubert, B., Mohr, C., Sturm, M., Feldhahn, M., and Kohlbacher, O. (2014). OptiType: precision HLA typing from next-generation sequencing data. Bioinformatics, 30(23), 3310-3316.
  14. Thiel, P, Sach-Peltason, L, Ottmann, C, and Kohlbacher, O (2014). Blocked Inverted Indices for Exact Clustering of Large Chemical Spaces. J. Chem. Inf. Model., 54(9):2395-401.
  15. Wagner, R, et al., (2014). Clinical and non-targeted metabolomic profiling of homozygous carries of Transcription Factor 7-like 2 variant rs7903146. Sci. Rep., 4:5296.
  16. Walzer, M, et al., (2014). qcML: an exchange format for quality control metrics from mass spectometry experiments. Mol. Cell. Prot., 13(8):1905-13.

 

 

2013

  1. Brand, L. H., Fischer, N. M., Harter, K., Kohlbacher, O., & Wanke, D. (2013). Elucidating the evolutionary conserved DNA-binding specificities of WRKY transcription factors by molecular dynamics and in vitro binding assays. Nucleic Acids Research, 41(21), 9764–9778.
  2. Gifford, C.A., et al. (2013). Transcriptional and epigenetic dynamics during specification of human embryonic stem cells. Cell. 153(5): p. 1149-63.
  3. Kyzirakos, C., Pflückhahn, U., Sturm, M., Schroeder, C., Bauer, P., Walter, M., Feld- hahn, M., Walzer, M., Mohr, C. et. al (2013). iVacALL: utilizing next- generation sequencing for the establishment of an individual peptide vaccination approach for paediatric acute lymphoblastic leukaemia. Bone Marrow Transplan- tation, 48, S401.
  4. Nahnsen, S., Bielow, C., Reinert, K., & Kohlbacher, O. (2013). Tools for Label-free Peptide Quantification. Molecular & Cellular Proteomics, 12(3), 549–556.
  5. Nahnsen, S., T. Sachsenberg, and O. Kohlbacher (2013), PTMeta: Increasing identification rates of modified peptides using modification prescanning and meta-analysis. Proteomics. 13(6): p. 1042-51.
  6. Perez-Riverol, Y., et al. (2013). Computational proteomics pitfalls and challenges: HavanaBioinfo 2012 workshop report. J Proteomics. 87: p. 134-8.
  7. Roosen-Runge, F., et al. (2013), Interplay of pH and binding of multivalent metal ions: charge inversion and reentrant condensation in protein solutions. J Phys Chem B. 117(18): p. 5777-87.
  8. Schubert, B., Lund, O., & Nielsen, M. (2013). Evaluation of peptide selection approaches for epitope-based vaccine design. Tissue Antigens, 82(4), 243–251.
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2012

  1. Ahrends, R., Lichtner, B., Buck, F., Hildebrand, D., Kotasinska, M., Kohlbacher, O., et al. (2012). Comparison of displacement versus gradient mode for separation of a complex protein mixture by anion-exchange chromatography. Journal of Chromatography B, 901, 34–40.
  2. Feldhahn, M., Dönnes, P., Schubert, B., Schilbach, K., Rammensee, H.-G., & Kohlbacher, O. (2012). miHA-Match: Computational detection of tissue-specific minor histocompatibility antigens. Journal of Immunological Methods, 386(1–2), 94–100.
  3. Hrabe, T., Chen, Y., Pfeffer, S., Kuhn Cuellar, L., Mangold, A.-V., & Förster, F. (2012). PyTom: A python-based toolbox for localization of macromolecules in cryo-electron tomograms and subtomogram analysis. Journal of Structural Biology, 178(2), 177–188.
  4. Junker, J., Bielow, C., Bertsch, A., Sturm, M., Reinert, K., & Kohlbacher, O. (2012). TOPPAS: A Graphical Workflow Editor for the Analysis of High-Throughput Proteomics Data. Journal of Proteome Research, 11(7), 3914–3920.
  5. Nahnsen, S., & Kohlbacher, O. (2012). In silico design of targeted SRM-based experiments. BMC Bioinformatics, 13(S16).
  6. Roglin, L., Thiel, P., Kohlbacher, O., & Ottmann, C. (2012). Covalent attachment of pyridoxal-phosphate derivatives to 14-3-3 proteins. Proceedings of the National Academy of Sciences, 109(18), E1051–E1053.