2024
Building and analyzing metacells in single-cell genomics data. Bilous M, Hérault L, Gabriel AA, Teleman M, Gfeller D. (2024) BioRxiv, 10.1101/2024.02.04.578815
Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells. Croce G, Bobisse S, Moreno DL, Schmidt J, Guillaume P, Harari A, Gfeller D. (2024) Nature Communications, 5(1):3211.
2023
How to predict binding specificity and ligands for new MHC-II alleles with MixMHC2pred. Racle J, Gfeller D. (2023) BioRxiv, 10.1101/2023.12.18.572125.
Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data. Gabriel AA, Racle J, Falquet M, Jandus C, Gfeller D. (2023) BioRxiv, 10.1101/2023.10.11.561826.
Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes. Racle J, Guillaume P, Schmidt J, Michaux J, Larabi A, Lau K, Perez MAS, Croce G, Genolet R, Coukos G, Zoete V, Pojer F, Bassani-Sternberg M, Harari A, Gfeller D. (2023) Immunity, 2023, 56, 1-17.
Neoantigen-specific CD8 T cells with high structural avidity preferentially reside in and eliminate tumors. Schmidt J, Chiffelle J, Perez MAS, Magnin M, Bobisse S, Arnaud M, Genolet R, Cesbron J, Barras D, Navarro Rodrigo B, Benedetti F, Michel A, Queiroz L, Baumgaertner P, Guillaume P, Hebeisen M, Michielin O, Nguyen-Ngoc T, Huber F, Irving M, Tissot-Renaud S, Stevenson BJ, Rusakiewicz S, Dangaj Laniti D, Bassani-Sternberg M, Rufer N, Gfeller D, Kandalaft LE, Speiser DE, Zoete V, Coukos G, Harari A. (2023) Nature Communications, 14(1):3188.
Contemplating immunopeptidomes to better predict them. Gfeller D, Liu Y, Racle J (2023) Seminars in Immunology, 66:101708.
Cancer vaccines based on whole-tumor lysate or neoepitopes with validated HLA binding outperform those with predicted HLA-binding affinity. Fritah H, Graciotti M, Chiang CL, Huguenin-Bergenat A, Petremand R, Ahmed R, Guillaume P, Schmidt J, Stevenson BJ, Gfeller D, Harari A, Kandalaft LE (2023) iScience, 26(4):106288.
Improved predictions of antigen presentation and TCR recognition with MixMHCpred2. 2 and PRIME2. 0 reveal potent SARS-CoV-2 CD8+ T-cell epitopes. Gfeller D, Schmidt J, Croce G, Guillaume P, Bobisse S, Genolet R, Queiroz L, Cesbron J, Racle J, Harari A. (2023), Cell Systems, 14, 72.
The MHC Motif Atlas: a database of MHC binding specificities and ligands. Tadros D, Eggenschwiler S, Racle J, Gfeller D. (2023) Nucleis Acids Research, 51 (D1), D428-D437.
2022
Rapid BCMA downmodulation on myeloma cells upon CAR T cell contact is mediated by trogocytosis and BCMA internalization. Camviel N, Wolf B, Croce G, Gfeller D, Zoete V, Arber C. (2022) Journal for ImmunoTherapy of Cancer, 10(11):e005091
Metacells untangle large and complex single-cell transcriptome networks. Bilous, M., Tran, L., Cianciaruso, C., Gabriel, A., Michel, H., Carmona, S. J., Pittet, M. J. , & Gfeller, D. (2022) BMC Bioinformatics, 23, 336, https://doi.org/10.1186/s12859-022-04861-1
Deciphering the landscape of phosphorylated HLA-II ligands. Solleder, M., Racle, J., Guillaume, Ph., Coukos, G., Bassani-Sternberg, M., & Gfeller, D. (2022) iScience. doi: https://doi.org/10.1101/2021.06.29.450288
Sensitive identification of neoantigens and cognate TCRs in human solid tumors. Arnaud M, Chiffelle J, Genolet R, Navarro Rodrigo B, Perez MAS, Huber F, Magnin M, Nguyen-Ngoc T, Guillaume P, Baumgaertner P, Chong C, Stevenson BJ, Gfeller D, Irving M, Speiser DE, Schmidt J, Zoete V, Kandalaft LE, Bassani-Sternberg M, Bobisse S, Coukos G, Harari A. (2022) Nature Biotechnology, doi: 10.1038/s41587-021-01072-6
2021
Nongenetic Evolution Drives Lung Adenocarcinoma Spatial Heterogeneity and Progression. Tavernari, D., Battistello, E., Dheilly, E., Petruzzella, A. S., Mina, M., Sordet-Dessimoz, J., Peters, S., Krueger, T., Gfeller, D., Riggi, N., Oricchio, E., Letovanec, I., & Ciriello, G. (2021). Cancer discovery, 11(6), 1490–1507. https://doi.org/10.1158/2159-8290.CD-20-1274
Prediction of neo-epitope immunogenicity reveals TCR recognition determinants and provides insight into immunoediting. Schmidt, J., Smith, A. R., Magnin, M., Racle, J., Devlin, J. R., Bobisse, S., Cesbron, J., Bonnet, V., Carmona, S. J., Huber, F., Ciriello, G., Speiser, D. E., Bassani-Sternberg, M., Coukos, G., Baker, B. M., Harari, A., & Gfeller, D. (2021). Cell reports. Medicine, 2(2), 100194. https://doi.org/10.1016/j.xcrm.2021.100194
Inflammatory B cells correlate with failure to checkpoint blockade in melanoma patients. de Jonge, K., Tillé, L., Lourenco, J., Maby-El Hajjami, H., Nassiri, S., Racle, J., Gfeller, D., Delorenzi, M., Verdeil, G., Baumgaertner, P., & Speiser, D. E. (2021). Oncoimmunology, 10(1), 1873585. https://doi.org/10.1080/2162402X.2021.1873585
Tumor-specific cytolytic CD4 T cells mediate immunity against human cancer. Cachot, A., Bilous, M., Liu, Y. C., Li, X., Saillard, M., Cenerenti, M., Rockinger, G. A., Wyss, T., Guillaume, P., Schmidt, J., Genolet, R., Ercolano, G., Protti, M. P., Reith, W., Ioannidou, K., de Leval, L., Trapani, J. A., Coukos, G., Harari, A., Speiser, D. E., Mathis, A., Gfeller, D., Altug, H. , Romero, P., & Jandus, C. (2021). Science advances, 7(9), eabe3348. https://doi.org/10.1126/sciadv.abe3348
2020
Structural dissimilarity from self drives neoepitope escape from immune tolerance. Devlin, J. R., Alonso, J. A., Ayres, C. M., Keller, G., Bobisse, S., Vander Kooi, C. W., Coukos, G., Gfeller, D., Harari, A., & Baker, B. M. (2020). Nature chemical biology, 16(11), 1269–1276. https://doi.org/10.1038/s41589-020-0610-1
Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction. Wells, D. K., van Buuren, M. M., Dang, K. K., Hubbard-Lucey, V. M., Sheehan, K., Campbell, K. M., Lamb, A., Ward, J. P., Sidney, J., Blazquez, A. B., Rech, A. J., Zaretsky, J. M., Comin-Anduix, B., Ng, A., Chour, W., Yu, T. V., Rizvi, H., Chen, J. M., Manning, P., Steiner, G. M., … Defranoux, N. A. (2020). Cell, 183(3), 818–834.e13. https://doi.org/10.1016/j.cell.2020.09.015
Single-cell transcriptomics identifies multiple pathways underlying antitumor function of TCR- and CD8αβ-engineered human CD4+ T cells. Rath, J. A., Bajwa, G., Carreres, B., Hoyer, E., Gruber, I., Martínez-Paniagua, M. A., Yu, Y. R., Nouraee, N., Sadeghi, F., Wu, M., Wang, T., Hebeisen, M., Rufer, N., Varadarajan, N., Ho, P. C., Brenner, M. K., Gfeller, D., & Arber, C. (2020). Science advances, 6(27), eaaz7809. https://doi.org/10.1126/sciadv.aaz7809
Cathepsin S Regulates Antigen Processing and T Cell Activity in Non-Hodgkin Lymphoma. Dheilly, E., Battistello, E., Katanayeva, N., Sungalee, S., Michaux, J., Duns, G., Wehrle, S., Sordet-Dessimoz, J., Mina, M., Racle, J., Farinha, P., Coukos, G., Gfeller, D., Mottok, A., Kridel, R., Correia, B. E., Steidl, C., Bassani-Sternberg, M., Ciriello, G., Zoete, V., & Oricchio, E. (2020). Cancer cell, 37(5), 674–689.e12. https://doi.org/10.1016/j.ccell.2020.03.016
Mass Spectrometry Based Immunopeptidomics Leads to Robust Predictions of Phosphorylated HLA Class I Ligands. Solleder, M., Guillaume, P., Racle, J., Michaux, J., Pak, H. S., Müller, M., Coukos, G., Bassani-Sternberg, M., & Gfeller, D. (2020). Molecular & cellular proteomics : MCP, 19(2), 390–404. https://doi.org/10.1074/mcp.TIR119.001641d.
Deciphering the transcriptomic landscape of tumor-infiltrating CD8 lymphocytes in B16 melanoma tumors with single-cell RNA-Seq. Carmona, S. J., Siddiqui, I., Bilous, M., Held, W., & Gfeller, D. (2020). Oncoimmunology, 9(1), 1737369. https://doi.org/10.1080/2162402X.2020.1737369
EPIC: A Tool to Estimate the Proportions of Different Cell Types from Bulk Gene Expression Data. Racle, J., & Gfeller, D. (2020). Methods in molecular biology (Clifton, N.J.), 2120, 233–248. https://doi.org/10.1007/978-1-0716-0327-7_17
2019
CD56 as a marker of an ILC1-like population with NK cell properties that is functionally impaired in AML. Salomé, B., Gomez-Cadena, A., Loyon, R., Suffiotti, M., Salvestrini, V., Wyss, T., Vanoni, G., Ruan, D. F., Rossi, M., Tozzo, A., Tentorio, P., Bruni, E., Riether, C., Jacobsen, E. M., Jandus, P., Conrad, C., Hoenig, M., Schulz, A., Michaud, K., Della Porta, M. G., Salvatore, S., Ho, P.-Ch., Gfeller, D., Ochsenbein, A., Mavilio, D., Curti, A., Marcenaro, E., Steinle, A., Horowitz, A., Romero, P., Trabanelli, S., & Jandus, C. (2019). Blood advances, 3(22), 3674–3687. https://doi.org/10.1182/bloodadvances.2018030478
Immunopeptidomics of colorectal cancer organoids reveals a sparse HLA class I neoantigen landscape and no increase in neoantigens with interferon or MEK-inhibitor treatment. Newey, A., Griffiths, B., Michaux, J., Pak, H. S., Stevenson, B. J., Woolston, A., Semiannikova, M., Spain, G., Barber, L. J., Matthews, N., Rao, S., Watkins, D., Chau, I., Coukos, G., Racle, J., Gfeller, D., Starling, N., Cunningham, D., Bassani-Sternberg, M., & Gerlinger, M. (2019). Journal for immunotherapy of cancer, 7(1), 309. https://doi.org/10.1186/s40425-019-0769-8
Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes. Racle, J., Michaux, J., Rockinger, G. A., Arnaud, M., Bobisse, S., Chong, C., Guillaume, P., Coukos, G., Harari, A., Jandus, C., Bassani-Sternberg, M., & Gfeller, D. (2019). Nature biotechnology, 37(11), 1283–1286. https://doi.org/10.1038/s41587-019-0289-6
A Phase Ib Study of the Combination of Personalized Autologous Dendritic Cell Vaccine, Aspirin, and Standard of Care Adjuvant Chemotherapy Followed by Nivolumab for Resected Pancreatic Adenocarcinoma—A Proof of Antigen Discovery Feasibility in Three Patients Bassani-Sternberg, M., Digklia, A., Huber, F., Wagner, D., Sempoux, C., Stevenson, B. J., Thierry, A. C., Michaux, J., Pak, H., Racle, J., Boudousquie, C., Balint, K., Coukos, G., Gfeller, D., Martin Lluesma, S., Harari, A., Demartines, N., & Kandalaft, L. E. (2019). Frontiers in immunology, 10, 1832. https://doi.org/10.3389/fimmu.2019.01832
Allosteric Modulation of Binding Specificity by Alternative Packing of Protein Cores. Ben-David, M., Huang, H., Sun, M., Corbi-Verge, C., Petsalaki, E., Liu, K., Gfeller, D., Garg, P., Tempel, W., Sochirca, I., Shifman, J. M., Davidson, A., Min, J., Kim, P. M., & Sidhu, S. S. (2019). Journal of molecular biology, 431(2), 336–350. https://doi.org/10.1016/j.jmb.2018.11.018
Intratumoral Tcf1+ PD-1+ CD8+ T Cells with Stem-like Properties Promote Tumor Control in Response to Vaccination and Checkpoint Blockade Immunotherapy. Siddiqui, I., Schaeuble, K., Chennupati, V., Fuertes Marraco, S. A., Calderon-Copete, S., Pais Ferreira, D., Carmona, S. J., Scarpellino, L., Gfeller, D., Pradervand, S., Luther, S. A., Speiser, D. E., & Held, W. (2019). Immunity, 50(1), 195–211.e10. https://doi.org/10.1016/j.immuni.2018.12.021Peer-reviewed.
Analysis of Secondary Structure Biases in Naturally Presented HLA-I Ligands. Perez, M., Bassani-Sternberg, M., Coukos, G., Gfeller, D., & Zoete, V. (2019). Frontiers in immunology, 10, 2731. https://doi.org/10.3389/fimmu.2019.02731
Computational KIR copy number discovery reveals interaction between inhibitory receptor burden and survival. Pyke, R. M., Genolet, R., Harari, A., Coukos, G., Gfeller, D., & Carter, H. (2019). Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 24, 148–159.
2018
The Length Distribution and Multiple Specificity of Naturally Presented HLA-I Ligands. Gfeller, D., Guillaume, P., Michaux, J., Pak, H. S., Daniel, R. T., Racle, J., Coukos, G., & Bassani-Sternberg, M. (2018). Journal of immunology (Baltimore, Md. : 1950), 201(12), 3705–3716. https://doi.org/10.4049/jimmunol.1800914
Estimating the Contribution of Proteasomal Spliced Peptides to the HLA-I Ligandome. Mylonas, R., Beer, I., Iseli, C., Chong, C., Pak, H. S., Gfeller, D., Coukos, G., Xenarios, I., Müller, M., & Bassani-Sternberg, M. (2018). Molecular & cellular proteomics : MCP, 17(12), 2347–2357. https://doi.org/10.1074/mcp.RA118.000877-reviewed.
The C-terminal extension landscape of naturally presented HLA-I ligands. Guillaume, P., Picaud, S., Baumgaertner, P., Montandon, N., Schmidt, J., Speiser, D. E., Coukos, G., Bassani-Sternberg, M., Filippakopoulos, P., & Gfeller, D. (2018). Proceedings of the National Academy of Sciences of the United States of America, 115(20), 5083–5088. https://doi.org/10.1073/pnas.1717277115
Polymorphic sites preferentially avoid co-evolving residues in MHC class I proteins. Dib, L., Salamin, N., & Gfeller, D. (2018). PLoS computational biology, 14(5), e1006188. https://doi.org/10.1371/journal.pcbi.1006188
Personalized cancer vaccine effectively mobilizes antitumor T cell immunity in ovarian cancer. Tanyi, J. L., Bobisse, S., Ophir, E., Tuyaerts, S., Roberti, A., Genolet, R., Baumgartner, P., Stevenson, B. J., Iseli, C., Dangaj, D., Czerniecki, B., Semilietof, A., Racle, J., Michel, A., Xenarios, I., Chiang, C., Monos, D. S., Torigian, D. A., Nisenbaum, H. L., Michielin, O., June, C. H., Levine, B. L., Powell Jr, D. J., Gfeller, D., Mick, R., Dafni, U., Zoete, V., Harari, A., Coukos, G., & Kandalaft, L. E. (2018). Science translational medicine, 10(436), eaao5931. https://doi.org/10.1126/scitranslmed.aao5931
Sensitive and frequent identification of high avidity neo-epitope specific CD8 + T cells in immunotherapy-naive ovarian cancer. Bobisse, S., Genolet, R., Roberti, A., Tanyi, J. L., Racle, J., Stevenson, B. J., Iseli, C., Michel, A., Le Bitoux, M. A., Guillaume, P., Schmidt, J., Bianchi, V., Dangaj, D., Fenwick, C., Derré, L., Xenarios, I., Michielin, O., Romero, P., Monos, D. S., Zoete, V., Gfeller, D., Kandalaft, L. E., Coukos, G., & Harari, A. (2018). Nature communications, 9(1), 1092. https://doi.org/10.1038/s41467-018-03301-0
High-throughput and Sensitive Immunopeptidomics Platform Reveals Profound Interferonγ-Mediated Remodeling of the Human Leukocyte Antigen (HLA) Ligandome. Chong, C., Marino, F., Pak, H., Racle, J., Daniel, R. T., Müller, M., Gfeller, D., Coukos, G., & Bassani-Sternberg, M. (2018). Molecular & cellular proteomics : MCP, 17(3), 533–548. https://doi.org/10.1074/mcp.TIR117.000383
Predicting Antigen Presentation-What Could We Learn From a Million Peptides? Gfeller, D., & Bassani-Sternberg, M. (2018). Frontiers in immunology, 9, 1716. https://doi.org/10.3389/fimmu.2018.01716
2017
Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data. Racle, J., de Jonge, K., Baumgaertner, P., Speiser, D. E., & Gfeller, D. (2017). eLife, 6, e26476. https://doi.org/10.7554/eLife.26476
Tumour-derived PGD2 and NKp30-B7H6 engagement drives an immunosuppressive ILC2-MDSC axis. Trabanelli, S., Chevalier, M. F., Martinez-Usatorre, A., Gomez-Cadena, A., Salomé, B., Lecciso, M., Salvestrini, V., Verdeil, G., Racle, J., Papayannidis, C., Morita, H., Pizzitola, I., Grandclément, C., Bohner, P., Bruni, E., Girotra, M., Pallavi, R., Falvo, P., Leibundgut, E. O., Baerlocher, G. M., Carlo-Stella, C., Taurino, D., Santoro, A., Spinelli, O., Rambaldi, A., Giarin, E., Basso, G., Tresoldi, C., Ciceri, F., Gfeller, D., Akdis, C. A., Mazzarella, L., Minucci, S., Pelicci, P. G, Marcenaro, E., McKenzie, A. N. J., Vanhecke, D., Coukos, G., Mavilio, D., Curti, A., Derré, L., & Jandus, C. (2017). Nature communications, 8(1), 593. https://doi.org/10.1038/s41467-017-00678-2
Identification of innate lymphoid cells in single-cell RNA-Seq data. Suffiotti, M., Carmona, S. J., Jandus, C., & Gfeller, D. (2017). Immunogenetics, 69(7), 439–450. https://doi.org/10.1007/s00251-017-1002-x
The pathogen-related yeast protein Pry1, a member of the CAP protein superfamily, is a fatty acid-binding protein. Darwiche, R., Mène-Saffrané, L., Gfeller, D., Asojo, O. A., & Schneiter, R. (2017). The Journal of biological chemistry, 292(20), 8304–8314. https://doi.org/10.1074/jbc.M117.781880
Broad and Conserved Immune Regulation by Genetically Heterogeneous Melanoma Cells. Neubert, N. J., Tillé, L., Barras, D., Soneson, C., Baumgaertner, P., Rimoldi, D., Gfeller, D., Delorenzi, M., Fuertes Marraco, S. A., & Speiser, D. E. (2017). Cancer research, 77(7), 1623–1636. https://doi.org/10.1158/0008-5472.CAN-16-2680-reviewed.
Single-cell transcriptome analysis of fish immune cells provides insight into the evolution of vertebrate immune cell types. Carmona, S. J., Teichmann, S. A., Ferreira, L., Macaulay, I. C., Stubbington, M. J., Cvejic, A., & Gfeller, D. (2017). Genome research, 27(3), 451–461. https://doi.org/10.1101/gr.207704.116
Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity. Bassani-Sternberg, M., Chong, C., Guillaume, P., Solleder, M., Pak, H., Gannon, P. O., Kandalaft, L. E., Coukos, G., & Gfeller, D. (2017). PLoS computational biology, 13(8), e1005725. https://doi.org/10.1371/journal.pcbi.1005725
ILC2-modulated T cell-to-MDSC balance is associated with bladder cancer recurrence. Chevalier, M. F., Trabanelli, S., Racle, J., Salomé, B., Cesson, V., Gharbi, D., Bohner, P., Domingos-Pereira, S., Dartiguenave, F., Fritschi, A. S., Speiser, D. E., Rentsch, C. A., Gfeller, D., Jichlinski, P., Nardelli-Haefliger, D., Jandus, C., & Derré, L. (2017). The Journal of clinical investigation, 127(8), 2916–2929. https://doi.org/10.1172/JCI89717
‘Hotspots’ of Antigen Presentation Revealed by Human Leukocyte Antigen Ligandomics for Neoantigen Prioritization. Müller, M., Gfeller, D., Coukos, G., & Bassani-Sternberg, M. (2017). Frontiers in immunology, 8, 1367. https://doi.org/10.3389/fimmu.2017.01367
2016
Unsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide-HLA Interactions. Bassani-Sternberg, M., & Gfeller, D. (2016). Journal of immunology (Baltimore, Md. : 1950), 197(6), 2492–2499. https://doi.org/10.4049/jimmunol.1600808
Current tools for predicting cancer-specific T cell immunity. Gfeller, D., Bassani-Sternberg, M., Schmidt, J., & Luescher, I. F. (2016). Oncoimmunology, 5(7), e1177691. https://doi.org/10.1080/2162402X.2016.1177691
The SIB Swiss Institute of Bioinformatics’ resources: focus on curated databases. SIB Swiss Institute of Bioinformatics Members (2016). Nucleic acids research, 44(D1), D27–D37. https://doi.org/10.1093/nar/gkv1310
2015
Protein homology reveals new targets for bioactive small molecules. Gfeller, D., & Zoete, V. (2015). Bioinformatics (Oxford, England), 31(16), 2721–2727. https://doi.org/10.1093/bioinformatics/btv214
2014
The caveolin-binding motif of the pathogen-related yeast protein Pry1, a member of the CAP protein superfamily, is required for in vivo export of cholesteryl acetate. Choudhary, V., Darwiche, R., Gfeller, D., Zoete, V., Michielin, O., & Schneiter, R. (2014). Journal of lipid research, 55(5), 883–894. https://doi.org/10.1194/jlr.M047126
A structural portrait of the PDZ domain family. Ernst, A., Appleton, B. A., Ivarsson, Y., Zhang, Y., Gfeller, D., Wiesmann, C., & Sidhu, S. S. (2014). Journal of molecular biology, 426(21), 3509–3519. https://doi.org/10.1016/j.jmb.2014.08.012
Prediction and experimental characterization of nsSNPs altering human PDZ-binding motifs. Gfeller, D., Ernst, A., Jarvik, N., Sidhu, S. S., & Bader, G. D. (2014). PloS one, 9(4), e94507. https://doi.org/10.1371/journal.pone.0094507
SwissTargetPrediction: a web server for target prediction of bioactive small molecules. Gfeller, D., Grosdidier, A., Wirth, M., Daina, A., Michielin, O., & Zoete, V. (2014). Nucleic acids research, 42(Web Server issue), W32–W38. https://doi.org/10.1093/nar/gku293
2013
Improving binding affinity and stability of peptide ligands by substituting glycines with D-amino acids. Chen, S., Gfeller, D., Buth, S. A., Michielin, O., Leiman, P. G., & Heinis, C. (2013). Chembiochem : a European journal of chemical biology, 14(11), 1316–1322. https://doi.org/10.1002/cbic.201300228
Shaping the interaction landscape of bioactive molecules. Gfeller, D., Michielin, O., & Zoete, V. (2013). Bioinformatics (Oxford, England), 29(23), 3073–3079. https://doi.org/10.1093/bioinformatics/btt540
SwissSidechain: a molecular and structural database of non-natural sidechains. Gfeller, D., Michielin, O., & Zoete, V. (2013). Nucleic acids research, 41(Database issue), D327–D332. https://doi.org/10.1093/nar/gks991
Susceptibility and adaptation to human TRIM5α alleles at positive selected sites in HIV-1 capsid. Rahm, N., Gfeller, D., Snoeck, J., Martinez, R., McLaren, P. J., Ortiz, M., Ciuffi, A., & Telenti, A. (2013). Virology, 441(2), 162–170. https://doi.org/10.1016/j.virol.2013.03.021
SH3 interactome conserves general function over specific form. Xin, X., Gfeller, D., Cheng, J., Tonikian, R., Sun, L., Guo, A., Lopez, L., Pavlenco, A., Akintobi, A., Zhang, Y., Rual, J. F., Currell, B., Seshagiri, S., Hao, T., Yang, X., Shen, Y. A., Salehi-Ashtiani, K., Li, J., Cheng, A. T., Bouamalay, D., Lugari, A., Hill, D. E., Grimes, M. L., Drubin, D. G., Grant, B. D., Vidal, M., Boone, Ch., Sidhu, S. S., & Bader, G. D. (2013). Molecular systems biology, 9, 652. https://doi.org/10.1038/msb.2013.9
2012
Sequence determinants of a microtubule tip localization signal (MtLS). Buey, R. M., Sen, I., Kortt, O., Mohan, R., Gfeller, D., Veprintsev, D., Kretzschmar, I., Scheuermann, J., Neri, D., Zoete, V., Michielin, O., de Pereda, J. M., Akhmanova, A., Volkmer, R., & Steinmetz, M. O. (2012). The Journal of biological chemistry, 287(34), 28227–28242. https://doi.org/10.1074/jbc.M112.373928
Uncovering new aspects of protein interactions through analysis of specificity landscapes in peptide recognition domains. Gfeller D. (2012). FEBS letters, 586(17), 2764–2772. https://doi.org/10.1016/j.febslet.2012.03.054
Expanding molecular modeling and design tools to non-natural sidechains. Gfeller, D., Michielin, O., & Zoete, V. (2012). Journal of computational chemistry, 33(18), 1525–1535. https://doi.org/10.1002/jcc.22982
MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets. Kim, T., Tyndel, M. S., Huang, H., Sidhu, S. S., Bader, G. D., Gfeller, D., & Kim, P. M. (2012). Nucleic acids research, 40(6), e47. https://doi.org/10.1093/nar/gkr1294.
Beyond the binding site: the role of the β₂-β₃ loop and extra-domain structures in PDZ domains. Mostarda, S., Gfeller, D., & Rao, F. (2012). PLoS computational biology, 8(3), e1002429. https://doi.org/10.1371/journal.pcbi.1002429
2011
The multiple-specificity landscape of modular peptide recognition domains. Gfeller, D., Butty, F., Wierzbicka, M., Verschueren, E., Vanhee, P., Huang, H., Ernst, A., Dar, N., Stagljar, I., Serrano, L., Sidhu, S. S., Bader, G. D., & Kim, P. M. (2011). Molecular systems biology, 7, 484. https://doi.org/10.1038/msb.2011.18
2010
Coevolution of PDZ domain-ligand interactions analyzed by high-throughput phage display and deep sequencing. Ernst, A., Gfeller, D., Kan, Z., Seshagiri, S., Kim, P. M., Bader, G. D., & Sidhu, S. S. (2010). Molecular bioSystems, 6(10), 1782–1790. https://doi.org/10.1039/c0mb00061b
Functional complexes between YAP2 and ZO-2 are PDZ domain-dependent, and regulate YAP2 nuclear localization and signalling. Oka, T., Remue, E., Meerschaert, K., Vanloo, B., Boucherie, C., Gfeller, D., Bader, G. D., Sidhu, S. S., Vandekerckhove, J., Gettemans, J., & Sudol, M. (2010). The Biochemical journal, 432(3), 461–472. https://doi.org/10.1042/BJ20100870
2009
How to visually interpret biological data using networks. Merico, D., Gfeller, D., & Bader, G. D. (2009). How to visually interpret biological data using networks. Nature biotechnology, 27(10), 921–924. https://doi.org/10.1038/nbt.1567
Bayesian modeling of the yeast SH3 domain interactome predicts spatiotemporal dynamics of endocytosis proteins. Tonikian, R., Xin, X., Toret, C. P., Gfeller, D., Landgraf, C., Panni, S., Paoluzi, S., Castagnoli, L., Currell, B., Seshagiri, S., Yu, H., Winsor, B., Vidal, M., Gerstein, M. B., Bader, G. D., Volkmer, R., Cesareni, G., Drubin, D. G., Kim, P. M., Sidhu, S. S., & Boone, C. (2009). PLoS biology, 7(10), e1000218. https://doi.org/10.1371/journal.pbio.1000218
2008
Spectral coarse graining and synchronization in oscillator networks. Gfeller, D., & De Los Rios, P. (2008). Physical review letters, 100(17), 174104. https://doi.org/10.1103/PhysRevLett.100.174104
2007
Uncovering the topology of configuration space networks. Gfeller, D., de Lachapelle, D. M., De Los Rios, P., Caldarelli, G., & Rao, F. (2007). Physical review. E, Statistical, nonlinear, and soft matter physics, 76(2 Pt 2), 026113. https://doi.org/10.1103/PhysRevE.76.026113
Spectral coarse graining of complex networks. Gfeller, D., & De Los Rios, P. (2007). Physical review letters, 99(3), 038701. https://doi.org/10.1103/PhysRevLett.99.038701
Complex network analysis of free-energy landscapes. Gfeller, D., De Los Rios, P., Caflisch, A., & Rao, F. (2007). Proceedings of the National Academy of Sciences of the United States of America, 104(6), 1817–1822. https://doi.org/10.1073/pnas.0608099104
2005
Finding instabilities in the community structure of complex networks. Gfeller, D., Chappelier, J. C., & De Los Rios, P. (2005). Physical review. E, Statistical, nonlinear, and soft matter physics, 72(5 Pt 2), 056135. https://doi.org/10.1103/PhysRevE.72.056135