Zentrum für Quantitative Biologie

Publikationen des QBiC

Vorabdrucke

  • Ballesio, F., Bangash, A. H., Barradas-Bautista, D., Barton, J., Guarracino, A., Heumos, L., Panoli, A., Pietrosanto, M., Togkousidis, A., Davis, P., & Psomopoulos, F. E. (2020). Determining a novel feature-space for SARS-CoV-2 sequence data. Center for Open Science. https://doi.org/10.37044/osf.io/xt7gw
  • Cardona Gloria, Y., Bernhart, S. H., Fillinger, S., Wolz, O.-O., Dickhöfer, S., Admard, J., Ossowski, S., Nahnsen, S., Siebert, R., & Weber, A. N. (2020). The failure of B cells to induce non-canonical MYD88 splice variants correlates with lymphomagenesis via sustained NF-κB signaling. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2020.06.18.154393
  • Ferrarini, M., Aguiar-Pulido, V., Dawson, E. T., Guarracino, A., Gruber, A., Heumos, L., Kanitz, A., Lal, A., Pickett, B. E., Rebollo, R., Ruiz-Arenas, C., Awe, O. I., Bedi, S., Busby, B., Georgaki, M., James, C., Gonzalez, I. M., Meldal, B., Mucha, S. G., … Tsagiopoulou, M. (2020). Global analysis of human SARS-CoV-2 infection and host-virus interaction. Center for Open Science. https://doi.org/10.37044/osf.io/b4zkp
  • Garrison, E., Guarracino, A., Heumos, S., Villani, F., Bao, Z., Tattini, L., Hagmann, J., Vorbrugg, S., Marco-Sola, S., Kubica, C., Ashbrook, D. G., Thorell, K., Rusholme-Pilcher, R. L., Liti, G., Rudbeck, E., Nahnsen, S., Yang, Z., Moses, M. N., Nobrega, F. L., … Prins, P. (2023). Building pangenome graphs. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2023.04.05.535718
  • 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
  • Heumos, S., Guarracino, A., Schmelzle, J.-N. M., Li, J., Zhang, Z., Hagmann, J., Nahnsen, S., Prins, P., & Garrison, E. (2023). Pangenome graph layout by Path-Guided Stochastic Gradient Descent. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2023.09.22.558964
  • Walker, A., Houwaart, T., …, Alexander T. Dilthey, German COVID-19 OMICS Initiative (DeCOI) (2021). Characterization of SARS-CoV-2 genetic structure and infection clusters in a large German city based on integrated genomic surveillance, outbreak analysis, and contact tracing. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2021.02.13.21251678
  • Wanner, J., Cuellar, L. K., Rausch, L., Berendzen, K. W., Wanke, F., Gabernet, G., Harter, K., & Nahnsen, S. (2023). nf-root: a best-practice pipeline for deep learning-based analysis of apoplastic pH in microscopy images of developmental zones in plant root tissue. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2023.01.16.524272

2024

  1. Baláž, A., Gagie, T., Goga, A., Heumos, S., Navarro, G., Petescia, A., & Sirén, J. (2024). Wheeler Maps. In Lecture Notes in Computer Science (pp. 178–192). Springer Nature Switzerland.
  2. Fang, X., Colina Blanco, A. E., Christl, I., Le Bars, M., Straub, D., Kleindienst, S., Planer-Friedrich, B., Zhao, F.-J., Kappler, A., & Kretzschmar, R. (2024). Simultaneously decreasing arsenic and cadmium in rice by soil sulfate and limestone amendment under intermittent flooding. In Environmental Pollution (Vol. 347, p. 123786). Elsevier BV.
  3. Grimm, H., Drabesch, S., Nicol, A., Straub, D., Joshi, P., Zarfl, C., Planer-Friedrich, B., Muehe, E. M., & Kappler, A. (2024). Arsenic immobilization and greenhouse gas emission depend on quantity and frequency of nitrogen fertilization in paddy soil. In Heliyon (Vol. 10, Issue 16, p. e35706). Elsevier BV.
  4. Grimm, H., Lorenz, J., Straub, D., Joshi, P., Shuster, J., Zarfl, C., Muehe, E. M., & Kappler, A. (2024). Nitrous oxide is the main product during nitrate reduction by a novel lithoautotrophic iron(II)-oxidizing culture from an organic-rich paddy soil. In A. Bose (Ed.), Applied and Environmental Microbiology. American Society for Microbiology
  5. Haluska, A. A., Röhler, K., Fabregat‐Palau, J., Alexandrino, D. A. M., Abramov, S., Thompson, K. J., Straub, D., Kleindienst, S., Bugsel, B., Zweigle, J., Zwiener, C., & Grathwohl, P. (2024). Complementary Field and Laboratory Batch Studies to Quantify Generation Rates of Perfluoroalkyl Acids in a Contaminated Agricultural Topsoil with Unknown Precursors. In Groundwater Monitoring & Remediation (Vol. 44, Issue 3, pp. 61–75). Wiley.
  6. Hanssen, F., Garcia, M. U., Folkersen, L., Pedersen, A. S., Lescai, F., Jodoin, S., Miller, E., Seybold, M., Wacker, O., Smith, N., Gabernet, G., & Nahnsen, S. (2024). Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery. In NAR Genomics and Bioinformatics (Vol. 6, Issue 2). Oxford University Press (OUP).
  7. Heumos, S., Heuer, M. L., Hanssen, F., Heumos, L., Guarracino, A., Heringer, P., Ehmele, P., Prins, P., Garrison, E., & Nahnsen, S. (2024). Cluster-efficient pangenome graph construction with nf-core/pangenome. In C. Alkan (Ed.), Bioinformatics. Oxford University Press (OUP)
  8. Jeyagaran, A., Urbanczyk, M., Carvajal‐Berrio, D., Baldissera, T., Kaiser, P. D., Kuhlburger, L., Czemmel, S., Nahnsen, S., Duffy, G. P., Brucker, S. Y., Layland, S. L., & Schenke‐Layland, K. (2024). ECM Proteins Nidogen‐1 and Decorin Restore Functionality of Human Islets of Langerhans upon Hypoxic Conditions. In Advanced Healthcare Materials. Wiley.
  9. Kaldjob-Heinrich, L., Nuciforo, S., Lemke, S., Stahl, A., Czemmel, S., Babaei, S., Blukacz, L., Meier, M.-A., Zhang, Y., Schürch, C. M., Gonzalez-Menendez, I., Woelffing, P., Malek, N. P., Scheble, V., Nahnsen, S., Claassen, M., Templin, M., Bösmüller, H., Heim, M. H., … Bitzer, M. (2024). ADENOSINE RECEPTOR 3 IN LIVER CANCER: EXPRESSION VARIABILITY, EPIGENETIC MODULATION, AND ENHANCED HDAC INHIBITOR EFFECTS. In Gastro Hep Advances. Elsevier BV.
  10. Langarica-Fuentes, A., Straub, D., Wimmer, B., Thompson, K., Nahnsen, S., Huhn, C., & Kleindienst, S. (2024). Subtle microbial community changes despite rapid glyphosate degradation in microcosms with four German agricultural soils. In Applied Soil Ecology (Vol. 198, p. 105381). Elsevier BV.
  11. Perelo, L. W., Gabernet, G., Straub, D., & Nahnsen, S. (2024). How tool combinations in different pipeline versions affect the outcome in RNA-seq analysis. In NAR Genomics and Bioinformatics (Vol. 6, Issue 1). Oxford University Press (OUP).
  12. Vogel, A. L., Thompson, K. J., Straub, D., Musat, F., Gutierrez, T., & Kleindienst, S. (2024). Genetic redundancy in the naphthalene-degradation pathway of Cycloclasticus pugetii strain PS-1 enables response to varying substrate concentrations. In FEMS Microbiology Ecology (Vol. 100, Issue 6). Oxford University Press (OUP).

2023

  1. Aly, A., Laszlo, Z. I., Rajkumar, S., Demir, T., Hindley, N., Lamont, D. J., Lehmann, J., Seidel, M., Sommer, D., Franz-Wachtel, M., Barletta, F., Heumos, S., Czemmel, S., Kabashi, E., Ludolph, A., Boeckers, T. M., Henstridge, C. M., & Catanese, A. (2023). Integrative proteomics highlight presynaptic alterations and c-Jun misactivation as convergent pathomechanisms in ALS. In Acta Neuropathologica. Springer Science and Business Media LLC.
  2. Begg, T. J. A., Schmidt, A., Kocher, A., Larmuseau, M. H. D., Runfeldt, G., Maier, P. A., Wilson, J. D., Barquera, R., Maj, C., Szolek, A., Sager, M., Clayton, S., Peltzer, A., Hui, R., Ronge, J., Reiter, E., Freund, C., Burri, M., Aron, F., … Krause, J. (2023). Genomic analyses of hair from Ludwig van Beethoven. In Current Biology. Elsevier BV.
  3. Chatziioannou, E., Roßner, J., Aung, T. N., Rimm, D. L., Niessner, H., Keim, U., Serna-Higuita, L. M., Bonzheim, I., Kuhn Cuellar, L., Westphal, D., Steininger, J., Meier, F., Pop, O. T., Forchhammer, S., Flatz, L., Eigentler, T., Garbe, C., Röcken, M., Amaral, T., & Sinnberg, T. (2023). Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases. In eBioMedicine (Vol. 93, p. 104644). Elsevier BV.
  4. Hakimzadeh, A., Abdala Asbun, A., Albanese, D., Bernard, M., Buchner, D., Callahan, B., Caporaso, J. G., Curd, E., Djemiel, C., Brandström Durling, M., Elbrecht, V., Gold, Z., Gweon, H. S., Hajibabaei, M., Hildebrand, F., Mikryukov, V., Normandeau, E., Özkurt, E., M. Palmer, J., … Anslan, S. (2023). A pile of pipelines: An overview of the bioinformatics software for metabarcoding data analyses. In Molecular Ecology Resources. Wiley.
  5. Heumos, L., Ehmele, P., Kuhn Cuellar, L., Menden, K., Miller, E., Lemke, S., Gabernet, G., & Nahnsen, S. (2023). mlf-core: a framework for deterministic machine learning. In J. Wren (Ed.), Bioinformatics (Vol. 39, Issue 4). Oxford University Press (OUP).
  6. Liao, W.-W., Asri, M., Ebler, J., Doerr, D., Haukness, M., Hickey, G., Lu, S., Lucas, J. K., Monlong, J., Abel, H. J., Buonaiuto, S., Chang, X. H., Cheng, H., Chu, J., Colonna, V., Eizenga, J. M., Feng, X., Fischer, C., Fulton, R. S., … Paten, B. (2023). A draft human pangenome reference. In Nature (Vol. 617, Issue 7960, pp. 312–324). Springer Science and Business Media LLC.
  7. Lu, L., Rughöft, S., Straub, D., Joye, S. B., Kappler, A., & Kleindienst, S. (2023). Rhamnolipid Biosurfactants Enhance Microbial Oil Biodegradation in Surface Seawater from the North Sea. In ACS ES&T Water (Vol. 3, Issue 8, pp. 2255–2266). American Chemical Society (ACS).
  8. Martínez-Acosta, M., Vázquez-Villegas, P., Mejía-Manzano, L. A., Soto-Inzunza, G. V., Ruiz-Aguilar, K. M., Kuhn Cuellar, L., Caratozzolo, P., & Membrillo-Hernández, J. (2023). The implementation of SDG12 in and from higher education institutions: universities as laboratories for generating sustainable cities. In Frontiers in Sustainable Cities (Vol. 5). Frontiers Media SA.
  9. Urbanczyk, M., Jeyagaran, A., Zbinden, A., Lu, C., Marzi, J., Kuhlburger, L., Nahnsen, S., Layland, S. L., Duffy, G., & Schenke-Layland, K. (2023). Decorin improves human pancreatic β-cell function and regulates ECM expression in vitro. In Matrix Biology (Vol. 115, pp. 160–183). Elsevier BV.
  10. Vogel, A. L., Thompson, K. J., Straub, D., App, C. B., Gutierrez, T., Löffler, F. E., & Kleindienst, S. (2023). Substrate-independent expression of key functional genes in Cycloclasticus pugetii strain PS-1 limits their use as markers for PAH biodegradation. In Frontiers in Microbiology (Vol. 14). Frontiers Media SA.

2022

  1. Antony, J. S., Daniel-Moreno, A., Lamsfus-Calle, A., Raju, J., Kaftancioglu, M., Ureña-Bailén, G., Rottenberger, J., Hou, Y., Santhanakumaran, V., Lee, J.-H., Heumos, L., Böhringer, J., Krägeloh-Mann, I., Handgretinger, R., & Mezger, M. (2022). A Mutation-Agnostic Hematopoietic Stem Cell Gene Therapy for Metachromatic Leukodystrophy. In The CRISPR Journal (Vol. 5, Issue 1, pp. 66–79). Mary Ann Liebert Inc.
  2. Abramov, S. M., Straub, D., Tejada, J., Grimm, L., Schädler, F., Bulaev, A., Thorwarth, H., Amils, R., Kappler, A., & Kleindienst, S. (2022). Biogeochemical Niches of Fe-Cycling Communities Influencing Heavy Metal Transport along the Rio Tinto, Spain. In J. D. Semrau (Ed.), Applied and Environmental Microbiology (Vol. 88, Issue 4). American Society for Microbiology.
  3. Guarracino, A., Heumos, S., Nahnsen, S., Prins, P., & Garrison, E. (2022). ODGI: understanding pangenome graphs. In P. Robinson (Ed.), Bioinformatics (Vol. 38, Issue 13, pp. 3319–3326). Oxford University Press (OUP).
  4. Huang, Y.-M., Jakus, N., Straub, D., Konstantinidis, K. T., Blackwell, N., Kappler, A., & Kleindienst, S. (2022). “Candidatus ferrigenium straubiae” sp. nov., “Candidatus ferrigenium bremense” sp. nov., “Candidatus ferrigenium altingense” sp. nov., are autotrophic Fe(II)-oxidizing bacteria of the family Gallionellaceae. Systematic and Applied Microbiology, 45(3).
  5. Khozooei, S., Lettau, K., Barletta, F., Jost, T., Rebholz, S., Veerappan, S., Franz-Wachtel, M., Macek, B., Iliakis, G., Distel, L. V., Zips, D., & Toulany, M. (2022). Fisetin induces DNA double-strand break and interferes with the repair of radiation-induced damage to radiosensitize triple negative breast cancer cells. In Journal of Experimental & Clinical Cancer Research (Vol. 41, Issue 1). Springer Science and Business Media LLC
  6. Krakau, S., Straub, D., Gourlé, H., Gabernet, G., & Nahnsen, S. (2022). nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning. NAR Genomics and Bioinformatics, 4(1).
  7. Kuhn Cuellar, L., Friedrich, A., Gabernet, G., de la Garza, L., Fillinger, S., Seyboldt, A., Koch, T., zur Oven-Krockhaus, S., Wanke, F., Richter, S., Thaiss, W. M., Horger, M., Malek, N., Harter, K., Bitzer, M., & Nahnsen, S. (2022). A data management infrastructure for the integration of imaging and omics data in life sciences. BMC Bioinformatics, 23(1).
  8. Muehler, D., Mao, X., Czemmel, S., Geißert, J., Engesser, C., Hiller, K.-A., Widbiller, M., Maisch, T., Buchalla, W., Al-Ahmad, A., & Cieplik, F. (2022). Transcriptomic Stress Response in Streptococcus mutans following Treatment with a Sublethal Concentration of Chlorhexidine Digluconate. In Microorganisms (Vol. 10, Issue 3, p. 561).
  9. Patzner, M. S., Kainz, N., Lundin, E., Barczok, M., Smith, C., Herndon, E., Kinsman-Costello, L., Fischer, S., Straub, D., Kleindienst, S., Kappler, A., & Bryce, C. (2022). Seasonal Fluctuations in Iron Cycling in Thawing Permafrost Peatlands. Environmental Science & Technology, 56(7), 4620–4631.
  10. Patzner, M. S., Logan, M., McKenna, A. M., Young, R. B., Zhou, Z., Joss, H., Mueller, C. W., Hoeschen, C., Scholten, T., Straub, D., Kleindienst, S., Borch, T., Kappler, A., & Bryce, C. (2022). Microbial iron cycling during palsa hillslope collapse promotes greenhouse gas emissions before complete permafrost thaw. Communications Earth & Environment, 3(1).
  11. Sun, B., Bhati, K. K., Song, P., Edwards, A., Petri, L., Kruusvee, V., Blaakmeer, A., Dolde, U., Rodrigues, V., Straub, D., Yang, J., Jia, G., & Wenkel, S. (2022). FIONA1-mediated methylation of the 3’UTR of FLC affects FLC transcript levels and flowering in Arabidopsis. In C. Köhler (Ed.), PLOS Genetics (Vol. 18, Issue 9, p. e1010386). Public Library of Science (PLoS).
  12. Van Le, A., Straub, D., Planer-Friedrich, B., Hug, S. J., Kleindienst, S., & Kappler, A. (2022). Microbial communities contribute to the elimination of As, Fe, Mn, and NH4+ from groundwater in household sand filters. In Science of The Total Environment (Vol. 838, p. 156496). Elsevier BV
  13. Vasseur, F., Cornet, D., Beurier, G., Messier, J., Rouan, L., Bresson, J., Ecarnot, M., Stahl, M., Heumos, S., Gérard, M., Reijnen, H., Tillard, P., Lacombe, B., Emanuel, A., Floret, J., Estarague, A., Przybylska, S., Sartori, K., Gillespie, L. M., … Violle, C. (2022). A Perspective on Plant Phenomics: Coupling Deep Learning and Near-Infrared Spectroscopy. In Frontiers in Plant Science (Vol. 13). Frontiers Media SA.

2021

  1. Cardona Gloria, Y., Bernhart, S. H., Fillinger, S., Wolz, O.-O., Dickhöfer, S., Admard, J., Ossowski, S., Nahnsen, S., Siebert, R., & Weber, A. N. R. (2021). Absence of Non-Canonical, Inhibitory MYD88 Splice Variants in B Cell Lymphomas Correlates With Sustained NF-κB Signaling. Frontiers in Immunology, 12.
  2. Fellows Yates, J. A., Lamnidis, T. C., Borry, M., Andrades Valtueña, A., Fagernäs, Z., Clayton, S., Garcia, M. U., Neukamm, J., & Peltzer, A. (2021). Reproducible, portable, and efficient ancient genome reconstruction with nf-core/eager. PeerJ, 9, e10947.
  3. Gerst, F., Kemter, E., Lorza-Gil, E., Kaiser, G., Fritz, A.-K., Nano, R., Piemonti, L., Gauder, M., Dahl, A., Nadalin, S., Königsrainer, A., Fend, F., Birkenfeld, A. L., Wagner, R., Heni, M., Stefan, N., Wolf, E., Häring, H.-U., & Ullrich, S. (2021). The hepatokine fetuin-A disrupts functional maturation of pancreatic beta cells. Diabetologia.
  4. Glodowska, M., Schneider, M., Eiche, E., Kontny, A., Neumann, T., Straub, D., Berg, M., Prommer, H., Bostick, B. C., Nghiem, A. A., Kleindienst, S., & Kappler, A. (2021). Fermentation, methanotrophy and methanogenesis influence sedimentary Fe and As dynamics in As-affected aquifers in Vietnam. Science of The Total Environment, 779, 146501.
  5. Glodowska, M., Schneider, M., Eiche, E., Kontny, A., Neumann, T., Straub, D., Kleindienst, S., & Kappler, A. (2021). Microbial transformation of biogenic and abiogenic Fe minerals followed by in-situ incubations in an As-contaminated vs. non-contaminated aquifer. Environmental Pollution, 281, 117012.
  6. Huang, Y.-M., Straub, D., Blackwell, N., Kappler, A., & Kleindienst, S. (2021). Meta-omics reveal Gallionellaceae and Rhodanobacter as interdependent key players for Fe(II) oxidation and nitrate reduction in the autotrophic enrichment culture KS. Applied and Environmental Microbiology.
  7. Huang, Y.-M., Straub, D., Kappler, A., Smith, N., Blackwell, N., & Kleindienst, S. (2021). A Novel Enrichment Culture Highlights Core Features of Microbial Networks Contributing to Autotrophic Fe(II) Oxidation Coupled to Nitrate Reduction. Microbial Physiology, 1–16.
  8. Jakus, N., Blackwell, N., Osenbrück, K., Straub, D., Byrne, J. M., Wang, Z., Glöckler, D., Elsner, M., Lueders, T., Grathwohl, P., Kleindienst, S., & Kappler, A. (2021). Nitrate Removal by a Novel Lithoautotrophic Nitrate-Reducing, Iron(II)-Oxidizing Culture Enriched from a Pyrite-Rich Limestone Aquifer. Applied and Environmental Microbiology, 87(16).
  9. Jakus, N., Blackwell, N., Straub, D., Kappler, A., & Kleindienst, S. (2021). Presence of Fe(II) and nitrate shapes aquifer-originating communities leading to an autotrophic enrichment dominated by a Fe(II)-oxidizing Gallionellaceae sp. In FEMS Microbiology Ecology. Oxford University Press (OUP).
  10. Krämer, B., Knoll, R., Bonaguro, L., ToVinh, M., Raabe, J., Astaburuaga-García, R., Schulte-Schrepping, J., Kaiser, K. M., Rieke, G. J., Bischoff, J., Monin, M. B., Hoffmeister, C., Schlabe, S., De Domenico, E., Reusch, N., Händler, K., Reynolds, G., Blüthgen, N., Hack, G., … Ziebuhr, J. (2021). Early IFN-α signatures and persistent dysfunction are distinguishing features of NK cells in severe COVID-19. In Immunity. Elsevier BV.
  11. Pienkowska, A., Glodowska, M., Mansor, M., Buchner, D., Straub, D., Kleindienst, S., & Kappler, A. (2021). Isotopic Labeling Reveals Microbial Methane Oxidation Coupled to Fe(III) Mineral Reduction in Sediments from an As-Contaminated Aquifer. Environmental Science & Technology Letters, 8(9), 832–837.
  12. Singh, Y., Trautwein, C., Fendel, R., Krickeberg, N., Berezhnoy, G., Bissinger, R., Ossowski, S., Salker, M. S., Casadei, N., Riess, O., Deutsche COVID-19 Omics Initiative (DeCOI) (2021). SARS-CoV-2 infection paralyzes cytotoxic and metabolic functions of the immune cells. Heliyon, e07147.
  13. Warnat-Herresthal, …, Deutsche COVID-19 Omics Initiative (DeCOI), …, Schultze, H. (2021). Swarm Learning for decentralized and confidential clinical machine learning. Nature, 594(7862), 265–270.
  14. Yang, Z., Sun, T., Kleindienst, S., Straub, D., Kretzschmar, R., Angenent, L. T., & Kappler, A. (2021). A Coupled Function of Biochar as Geobattery and Geoconductor Leads to Stimulation of Microbial Fe(III) Reduction and Methanogenesis in a Paddy Soil Enrichment Culture. Soil Biology and Biochemistry, 108446.

2020

  1. 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.
  2. Blackwell, N., Bryce, C., Straub, D., Kappler, A., & Kleindienst, S. (2020). Genomic insights into two novel Zetaproteobacteria Fe(II)-oxidizing isolates reveal lifestyle adaption to coastal marine sediments. Applied and Environmental Microbiology.
  3. 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.
  4. Eizenga, J. M., Novak, A. M., Kobayashi, E., Villani, F., Cisar, C., Heumos, S., Hickey, G., Colonna, V., Paten, B., & Garrison, E. (2020). Efficient dynamic variation graphs. In P. Robinson (Ed.), Bioinformatics (Vol. 36, Issue 21, pp. 5139–5144). Oxford University Press (OUP).
  5. Eizenga, J. M., Novak, A. M., Sibbesen, J. A., Heumos, S., Ghaffaari, A., Hickey, G., Chang, X., Seaman, J. D., Rounthwaite, R., Ebler, J., Rautiainen, M., Garg, S., Paten, B., Marschall, T., Sirén, J., & Garrison, E. (2020). Pangenome Graphs. In Annual Review of Genomics and Human Genetics (Vol. 21, Issue 1, pp. 139–162). Annual Reviews.
  6. 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.
  7. 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.
  8. Glodowska, M., Stopelli, E., Schneider, M., Rathi, B., Straub, D., Lightfoot, A., Kipfer, R., Berg, M., Jetten, M., Kleindienst, S., & Kappler, A. (2020). Arsenic mobilization by anaerobic iron-dependent methane oxidation. Communications Earth & Environment, 1, 42.
  9. Glodowska, M., Stopelli, E., Straub, D., Vu Thi, D., Trang, P. T. K., Viet, P. H., AdvectAs team members, Berg, M., Kappler, A., & Kleindienst, S. (2020). Arsenic behavior in groundwater in Hanoi (Vietnam) influenced by a complex biogeochemical network of iron, methane, and sulfur cycling. Journal of Hazardous Materials, 124398.
  10. Gugel, I., Ebner, F. H., Grimm, F., Czemmel, S., Paulsen, F., Hagel, C., Tatagiba, M., Nahnsen, S., & Tabatabai, G. (2020). Contribution of mTOR and PTEN to Radioresistance in Sporadic and NF2-Associated Vestibular Schwannomas: A Microarray and Pathway Analysis. Cancers, 12(1), 177.
  11. Koch, M. S., Czemmel, S., Lennartz, F., Beyeler, S., Rajaraman, S., Przystal, J. M., Govindarajan, P., Canjuga, D., Neumann, M., Rizzu, P., Zwirner, S., Hoetker, M. S., Zender, L., Walter, B., Tatagiba, M., Raineteau, O., Heutink, P., Nahnsen, S., & Tabatabai, G. (2020). Experimental glioma with high bHLH expression harbor increased replicative stress and are sensitive toward ATR inhibition. Neuro-Oncology Advances, 2(1).
  12. 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.
  13. Lamsfus-Calle, A., Daniel-Moreno, A., Antony, J. S., Epting, T., Heumos, L., Baskaran, P., … Mezger, M. (2020). Comparative targeting analysis of KLF1, BCL11A, and HBG1/2 in CD34+ HSPCs by CRISPR/Cas9 for the induction of fetal hemoglobin. Scientific Reports, 10(1).
  14. Ostroumov, D., Duong, S., Wingerath, J., Woller, N., Manns, M. P., Timrott, K., Kleine, M., Ramackers, W., Roessler, S., Nahnsen, S., Czemmel, S., Dittrich‐Breiholz, O., Eggert, T., Kühnel, F., & Wirth, T. C. (2020). Transcriptome profiling identifies TIGIT as a marker of T cell exhaustion in liver cancer. Hepatology.
  15. Paguem, A., Abanda, B., Achukwi, M. D., Baskaran, P., Czemmel, S., Renz, A., & Eisenbarth, A. (2020). Whole genome characterization of autochthonous Bos taurus brachyceros and introduced Bos indicus indicus cattle breeds in Cameroon regarding their adaptive phenotypic traits and pathogen resistance. BMC Genetics, 21(1).
  16. Ruschil, C., Gabernet, G., Lepennetier, G., Heumos, S., Kaminski, M., Hracsko, Z., Irmler, M., Beckers, J., Ziemann, U., Nahnsen, S., Owens, G. P., Bennett, J. L., Hemmer, B., & Kowarik, M. C. (2020). Specific Induction of Double Negative B Cells During Protective and Pathogenic Immune Responses. In Frontiers in Immunology (Vol. 11). Frontiers Media SA.
  17. Straub, D., Blackwell, N., Langarica-Fuentes, A., Peltzer, A., Nahnsen, S., & Kleindienst, S. (2020). Interpretations of Environmental Microbial Community Studies Are Biased by the Selected 16S rRNA (Gene) Amplicon Sequencing Pipeline. Frontiers in Microbiology.

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. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. Schubert, B, Brachvogel, H, Jürges, C, and Kohlbacher, O (2015). EpiToolKit - A Web-based Workbench for Vaccine Design. Bioinformatics, 31(13):2211-3.
  11. 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.
  12. 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.
  13. 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. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  9. Thiel, P., et al. (2013). Virtual screening and experimental validation reveal novel small-molecule inhibitors of 14-3-3 protein-protein interactions. Chem Commun (Camb). 49(76): p. 8468-70.
  10. Walzer, M., et al. (2013). The mzQuantML data standard for mass spectrometry-based quantitative studies in proteomics. Mol Cell Proteomics, 2013. 12(8): p. 2332-40.
  11. Ziller, M.J., et al. (2013). Charting a dynamic DNA methylation landscape of the human genome. Nature. 500(7463): p. 477-81.

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. 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.
  4. Nahnsen, S., & Kohlbacher, O. (2012). In silico design of targeted SRM-based experiments. BMC Bioinformatics, 13(S16).
  5. 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.