For all publications please see: https://orcid.org/0000-0002-2779-7174
Publications
2024
Scholarly publications
Lakbir, S., Buranelli, C., Meijer, G. A., Heringa, J., Fijneman, R. J. A., & Abeln, S. (2024). CIBRA identifies genomic alterations with a system-wide impact on tumor biology.
Dusoswa, S. A., Verhoeff, J., van Asten, S., Lübbers, J., van den Braber, M., Peters, S., Abeln, S., Crommentuijn, M. H. W., Wesseling, P., Vandertop, W. P., Twisk, J. W. R., Würdinger, T., Noske, D., van Kooyk, Y., & Garcia-Vallejo, J. J. (2024). The immunological landscape of peripheral blood in glioblastoma patients and immunological consequences of age and dexamethasone treatment. Frontiers in Immunology, 15, Article 1343484. https://doi.org/10.3389/fimmu.2024.1343484
2023
Scholarly publications
Gavaldá-Garciá, J., Stringer, B., Ivanova, O., Abeln, S., Feenstra, K. A., & Mouhib, H. (2023). Data Resources for Structural Bioinformatics. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02171
Waury, K., Gogishvili, D., Nieuwland, R., Chatterjee, M., Teunissen, C. E., & Abeln, S. (2023). Proteome encoded determinants of protein sorting into extracellular vesicles. (pp. 1-22). bioRxiv. https://doi.org/10.1101/2023.02.01.526570
Rubio-Alarcon, C., Stelloo, E., Vessies, D. C., van ‘t Erve, I., Mekkes, N., Swennenhuis, J., Lakbir, S., van Bree, E., Tijssen, M., Delis-van Diemen, P., Lanfermeijer, M., Linders, T. C., van den Broek, D., Punt, C. J., Heringa, J., Meijer, G. A., Abeln, S., Feitsma, H., & Fijneman, R. J. (2023). Abstract 222: High frequency of structural variants in FFPE colorectal cancer tissue detected by targeting selected common fragile site genes and LINE transposable elements. 222-222. https://doi.org/10.1158/1538-7445.am2023-222
Gils, J. H. M. V., Mouhib, H., Dijk, E. V., Dijkstra, M., Houtkamp, I., Goetzee, A., Abeln, S., & Feenstra, K. A. (2023). Thermodynamics of Protein Folding. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02175
Ivanova, O., Gavaldá-Garciá, J., Gogishvili, D., Houtkamp, I., Bouwmeester, R., Feenstra, K. A., & Abeln, S. (2023). Structure Alignment. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02170
Gils, J. H. M. V., Dijkstra, M., Mouhib, H., Rauh, A. S., Vreede, J., Feenstra, K. A., & Abeln, S. (2023). Monte Carlo for Protein Structures. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02177
Mouhib, H., Gils, J. H. M. V., Gavaldá-Garciá, J., Hou, Q., May, A., Rauh, A. S., Vreede, J., Abeln, S., & Feenstra, K. A. (2023). Molecular Dynamics. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02176
Jacobsen, A., Dijk, E. V., Mouhib, H., Stringer, B., Ivanova, O., Gavaldá-Garciá, J., Hoekstra, L., Feenstra, K. A., & Abeln, S. (2023). Introduction to Protein Structure. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02169
Gils, J. H. M. V., Dijk, E. V., May, A., Mouhib, H., Bijlard, J., Jacobsen, A., Houtkamp, I., Feenstra, K. A., & Abeln, S. (2023). Introduction to Protein Folding. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02174
Stringer, B., Jacobsen, A., Hou, Q., Ferrante, H. D., Ivanova, O., Waury, K., Gavaldá-Garciá, J., Abeln, S., & Feenstra, K. A. (2023). Function Prediction. In Introduction to Structural Bioinformatics https://doi.org/10.48550/arXiv.2307.02173
Gogishvili, D., Illes-Toth, E., J, MH., Hopley, C., E, CT., & Abeln, S. (2023). Structural flexibility and heterogeneity of recombinant human glial fibrillary acidic protein (GFAP). Proteins: Structure, Function and Bioinformatics. Advance online publication. https://doi.org/10.1002/prot.26656
Teunissen, C. E., Kimble, L., Bayoumy, S., Bolsewig, K., Burtscher, F., Coppens, S., Das, S., Gogishvili, D., Gomes, B. F., de San José, N. G., Mavrina, E., Meda, F. J., Mohaupt, P., Mravinacová, S., Waury, K., Wojdała, A. L., Abeln, S., Chiasserini, D., Hirtz, C., ... Zetterberg, H. (2023). Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias. Molecular and Cellular Proteomics, 22(10), Article 100629. https://doi.org/10.1016/j.mcpro.2023.100629
Bridel, C., Gils, J. H. M. V., Miedema, S. S. M., Hoozemans, J. J. M., Pijnenburg, Y. A. L., Smit, A. B., Rozemuller, A. J. M., Abeln, S., & Teunissen, C. E. (2023). Clusters of co-abundant proteins in the brain cortex associated with fronto-temporal lobar degeneration. Alzheimer's Research and Therapy, 15(1), Article 59. https://doi.org/10.1186/s13195-023-01200-1
https://dspace.library.uu.nl/bitstream/handle/1874/434515/s13195-023-01200-1.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/434515/s13195-023-01200-1.pdf?sequence=1
Gogishvili, D., Vromen, E. M., Hertog, S. K., Lemstra, A. W., Pijnenburg, Y. A. L., Visser, P. J., Tijms, B. M., Campo, M. D., Abeln, S., Teunissen, C. E., & Vermunt, L. (2023). Discovery of novel CSF biomarkers to predict progression in dementia using machine learning. Scientific Reports, 13(1), Article 6531. https://doi.org/10.1038/s41598-023-33045-x
https://dspace.library.uu.nl/bitstream/handle/1874/434514/s41598-023-33045-x.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/434514/s41598-023-33045-x.pdf?sequence=1
Waury, K., de WIt, R., Verberk, IMW., Teunissen, CE., & Abeln, S. (2023). Deciphering Protein Secretion from the Brain to Cerebrospinal Fluid for Biomarker Discovery. Journal of Proteome Research, 22(9), 3068-3080. https://doi.org/10.1021/acs.jproteome.3c00366
https://dspace.library.uu.nl/bitstream/handle/1874/434513/waury-et-al-2023-deciphering-protein-secretion-from-the-brain-to-cerebrospinal-fluid-for-biomarker-discovery.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/434513/waury-et-al-2023-deciphering-protein-secretion-from-the-brain-to-cerebrospinal-fluid-for-biomarker-discovery.pdf?sequence=1
2022
Scholarly publications
Stringer, B., de Ferrante, H., Abeln, S., Heringa, J., Feenstra, K. A., & Haydarlou, R. (2022). PIPENN: protein interface prediction from sequence with an ensemble of neural nets. Bioinformatics (Oxford, England), 38(8), 2111-2118. https://doi.org/10.1093/bioinformatics/btac071
Verhoeff, J., Abeln, S., & Garcia-Vallejo, J. J. (2022). INFLECT: an R-package for cytometry cluster evaluation using marker modality. BMC Bioinformatics, 23(1), 487. https://doi.org/10.1186/s12859-022-05018-w
Lakbir, S., Lahoz, S., Cuatrecasas, M., Camps, J., Glas, R. A., Heringa, J., Meijer, G. A., Abeln, S., & Fijneman, R. J. A. (2022). Tumour break load is a biologically relevant feature of genomic instability with prognostic value in colorectal cancer. European Journal of Cancer, 177, 94-102. https://doi.org/10.1016/j.ejca.2022.09.034
Halma, M. T. J., Wever, M. J. A., Abeln, S., Roche, D., & Wuite, G. J. L. (2022). Therapeutic potential of compounds targeting SARS-CoV-2 helicase. Frontiers in Chemistry, 10, 1-12. https://doi.org/10.3389/fchem.2022.1062352
Waury, K., Willemse, E. A. J., Vanmechelen, E., Zetterberg, H., Teunissen, C. E., & Abeln, S. (2022). Bioinformatics tools and data resources for assay development of fluid protein biomarkers. Biomarker Research, 10(1), Article 83. https://doi.org/10.1186/s40364-022-00425-w
Crusoe, M. R., Abeln, S., Iosup, A., Amstutz, P., Chilton, J., Tijanić, N., Ménager, H., Soiland-Reyes, S., & Goble, C. (2022). Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language. Communications of the ACM, 65(6), 54-63. https://doi.org/10.1145/3486897
https://dspace.library.uu.nl/bitstream/handle/1874/434518/3486897.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/434518/3486897.pdf?sequence=1
Gils, J. H. M. V., Gogishvili, D., Eck, J. V., Bouwmeester, R., Dijk, E. V., Abeln, S., & Gromiha, M. (Ed.) (2022). How sticky are our proteins? Quantifying hydrophobicity of the human proteome. Bioinformatics Advances, 2(1). https://doi.org/10.1093/bioadv/vbac002
https://dspace.library.uu.nl/bitstream/handle/1874/434517/vbac002.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/434517/vbac002.pdf?sequence=1
Capel, H., Feenstra, A., & Abeln, S. (2022). Multi-task learning to leverage partially annotated data for PPI interface prediction. Scientific Reports, 12. https://doi.org/10.1038/s41598-022-13951-2
https://dspace.library.uu.nl/bitstream/handle/1874/434516/s41598-022-13951-2.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/434516/s41598-022-13951-2.pdf?sequence=1
2021
Scholarly publications
Mouhib, H., Stringer, B., Ingen, H. V., Gavaldá-García, J., Waury, K., Abeln, S., & Feenstra, K. A. (2021). Structure determination. In Introduction to Protein Structural Bioinformatics
Hou, Q., Stringer, B., Waury, K., Capel, H., Haydarlou, R., Xue, F., Abeln, S., Heringa, J., & Feenstra, K. A. (2021). SeRenDIP-CE: sequence-based interface prediction for conformational epitopes. Bioinformatics (Oxford, England), 37(20), 3421-3427. https://doi.org/10.1093/bioinformatics/btab321
2020
Scholarly publications
Gils, J. H. M. V., Dijk, E. V., Peduzzo, A., Hofmann, A., Vettore, N., Schützmann, M. P., Groth, G., Mouhib, H., Otzen, D. E., Buell, A. K., & Abeln, S. (2020). The hydrophobic effect characterises the thermodynamic signature of amyloid fibril growth. PLoS Computational Biology, 16(5). https://doi.org/10.1371/journal.pcbi.1007767
https://dspace.library.uu.nl/bitstream/handle/1874/434519/The_hydrophobic_effect_characterises_the_thermodynamic_signature_of_amyloid_fibril_growth.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/434519/The_hydrophobic_effect_characterises_the_thermodynamic_signature_of_amyloid_fibril_growth.pdf?sequence=1
2019
Scholarly publications
Abeln, S., Feenstra, K. A., & Heringa, J. (2019). Protein three-dimensional structure prediction. In S. Ranganathan (Ed.), Encyclopedia of Bioinformatics and Computational Biology (Vol. 2, pp. 497-511). Elsevier. https://doi.org/10.1016/B978-0-12-809633-8.20505-0
Mouhib, H., Higuchi, A., Abeln, S., Yura, K., & Feenstra, K. A. (2019). Impact of pathogenic mutations of the GLUT1 glucose transporter on channel dynamics using consdyn enhanced sampling [version 1; peer review: 1 approved with reservations, 1 not approved]. F1000Research, 8, 1-14. https://doi.org/10.12688/f1000research.18553.1
Fijneman, R. J. A., Mekkes, N., Broek, E. V. D., Stringer, B., Glas, R. A., Komor, M. A., Rausch, C., Lieshout, S. V., Cuppen, E., Smith, M. L., Sebra, R. P., Rowell, W. J., Ashby, M., Carvalho, B., Heringa, J., Meijer, G. A., & Abeln, S. (2019). Abstract 1738: Characterization of structural variants within MACROD2 in the pathogenesis of colorectal cancer. https://doi.org/10.1158/1538-7445.am2019-1738
Willems, S. M., Abeln, S., Feenstra, K. A., de Bree, R., van der Poel, E. F., Baatenburg de Jong, R. J., Heringa, J., & van den Brekel, M. W. M. (2019). The potential use of big data in oncology. Oral Oncology, 98, 8-12. https://doi.org/10.1016/j.oraloncology.2019.09.003
Hou, Q., De Geest, P. F. G., Griffioen, C. J., Abeln, S., Heringa, J., & Feenstra, K. A. (2019). SeRenDIP: SEquential REmasteriNg to DerIve profiles for fast and accurate predictions of PPI interface positions. Bioinformatics, 35(22), 4794-4796. https://doi.org/10.1093/bioinformatics/btz428
Dijkstra, M. J. J., van der Ploeg, A. J., Feenstra, K. A., Fokkink, W. J., Abeln, S., & Heringa, J. (2019). Tailor-made multiple sequence alignments using the PRALINE 2 alignment toolkit. Bioinformatics (Oxford, England), 35(24), 5315-5317. https://doi.org/10.1093/bioinformatics/btz572
2018
Scholarly publications
Jacobsen, A., Bosch, L. J. W., Martens-De Kemp, S. R., Carvalho, B., Sillars-Hardebol, A. H., Dobson, R. J., De Rinaldis, E., Meijer, G. A., Abeln, S., Heringa, J., Fijneman, R. J. A., & Feenstra, K. A. (2018). Aurora kinase A (AURKA) interaction with Wnt and Ras-MAPK signalling pathways in colorectal cancer. Scientific Reports, 8(1), Article 7522. https://doi.org/10.1038/s41598-018-24982-z
Anton Feenstra, K., Abeln, S., Westerhuis, J. A., Brancos Dos Santos, F., Molenaar, D., Teusink, B., Hoefsloot, H. C. J., & Heringa, J. (2018). Training for translation between disciplines: A philosophy for life and data sciences curricula. Bioinformatics, 34(13), i4-i12. https://doi.org/10.1093/bioinformatics/bty233
Dijkstra, M., Bawono, P., Abeln, S., Feenstra, K. A., Fokkink, W., & Heringa, J. (2018). Motif-Aware PRALINE: Improving the alignment of motif regions: Improving the alignment of motif regions. PLoS Computational Biology, 14(11), 1-19. https://doi.org/10.1371/journal.pcbi.1006547
Dijkstra, M. J. J., Fokkink, W. J., Heringa, J., van Dijk, E., & Abeln, S. (2018). The characteristics of molten globule states and folding pathways strongly depend on the sequence of a protein. Molecular Physics, 116(21-22), 3173-3180. https://doi.org/10.1080/00268976.2018.1496290
2017
Scholarly publications
Broek, E. V. D., Dijkstra, M. J. J., Voorham, Q. J. M., Carvalho, B., Wiel, M. A. V. D., Abeln, S., Meijer, G. A., & Fijneman, R. J. A. (2017). Detection of structural variants and recurrent breakpoint genes in colorectal adenoma-to-carcinoma progression. Cancer Research, 77(3_Supplement), Article A07. https://doi.org/10.1158/1538-7445.CRC16-A07
Fijneman, R. J. A., van den Broek, E., van Lieshout, S., Rausch, C., Ylstra, B., van de Wiel, M. A., Meijer, G. A., & Abeln, S. (2017). GeneBreak: Detection of recurrent DNA copy number aberration-associated chromosomal breakpoints within genes. F1000Research, 5, Article 2340. https://doi.org/10.12688/f1000research.9259.2
Bawono, P., Dijkstra, M., Pirovano, W., Feenstra, A., Abeln, S., & Heringa, J. (2017). Multiple sequence alignment. In Methods in Molecular Biology (pp. 167-189). (Methods in Molecular Biology; Vol. 1525). Humana Press. https://doi.org/10.1007/978-1-4939-6622-6_8
Zhang, C., Bijlard, J., Staiger, C., Scollen, S., van Enckevort, D., Hoogstrate, Y., Senf, A., Hiltemann, S., Repo, S., Pipping, W., Bierkens, M., Payralbe, S., Stringer, B., Heringa, J., Stubbs, A., Bonino Da Silva Santos, L. O., Belien, J., Weistra, W., Azevedo, R., ... Abeln, S. (2017). Systematically linking tranSMART, Galaxy and EGA for reusing human translational research data. F1000Research, 6, Article 1488. https://doi.org/10.12688/f1000research.12168.1
2016
Scholarly publications
May, A., Brandt, B. W., El-Kebir, M., Klau, G. W., Zaura, E., Crielaard, W., Heringa, J., & Abeln, S. (2016). MetaModules identifies key functional subnetworks in microbiome-related disease. Bioinformatics, 32(11), 1678-1685. https://doi.org/10.1093/bioinformatics/btv526
Spalding, D., Hoogstrate, Y., Zhang, C., Senf, A., Bijlard, J., Hiltemann, S., van Enckevort, D., Repo, S., Heringa, J., Jenster, G., Fijneman, R. J. A., Boiten, J. W., Meijer, G. A., Stubbs, A., Rambla, J., & Abeln, S. (2016). Integration of EGA secure data access into Galaxy. F1000Research, 5, Article 2841. https://doi.org/10.12688/f1000research.10221.1
Haydarlou, R., Jacobsen, A., Bonzanni, N., Feenstra, K. A., Abeln, S., & Heringa, J. (2016). BioASF: A framework for automatically generating executable pathway models specified in BioPAX. Bioinformatics, 32(12), i60-i69. https://doi.org/10.1093/bioinformatics/btw250
Stringer, B., Meroño-Peñuela, A., Abeln, S., Van Harmelen, F., & Heringa, J. (2016). SCRY: Extending SPARQL with custom data processing methods for the life sciences. CEUR Workshop Proceedings, 1795.
Baclayon, M., Van Ulsen, P., Mouhib, H., Shabestari, M. H., Verzijden, T., Abeln, S., Roos, W. H., & Wuite, G. J. L. (2016). Mechanical Unfolding of an Autotransporter Passenger Protein Reveals the Secretion Starting Point and Processive Transport Intermediates. ACS Nano, 10(6), 5710-5719. https://doi.org/10.1021/acsnano.5b07072
Rajendran, R., May, A., Sherry, L., Kean, R., Williams, C., Jones, B. L., Burgess, K. V., Heringa, J., Abeln, S., Brandt, B. W., Munro, C. A., & Ramage, G. (2016). Integrating Candida albicans metabolism with biofilm heterogeneity by transcriptome mapping. Scientific Reports, 6, Article 35436. https://doi.org/10.1038/srep35436
Van Dijk, E., Varilly, P., Knowles, T. P. J., Frenkel, D., & Abeln, S. (2016). Consistent Treatment of Hydrophobicity in Protein Lattice Models Accounts for Cold Denaturation. Physical Review Letters, 116(7), Article 078101. https://doi.org/10.1103/PhysRevLett.116.078101
Heringa, J., Reinders, M., Abeln, S., & De Ridder, J. (2016). ECCB 2016: The 15th European Conference on Computational Biology. Bioinformatics, 32(17), i389-i392. https://doi.org/10.1093/bioinformatics/btw481
2015
Scholarly publications
May, A., Abeln, S., Buijs, M. J., Heringa, J., Crielaard, W., & Brandt, B. W. (2015). NGS-eval: NGS error analysis and novel sequence VAriant detection tooL. Nucleic Acids Research, 43(W1), W301-W305. https://doi.org/10.1093/nar/gkv346
Van Den Broek, E., Dijkstra, M. J. J., Krijgsman, O., Sie, D., Haan, J. C., Traets, J. J. H., Van De Wiel, M. A., Nagtegaal, I. D., Punt, C. J. A., Carvalho, B., Ylstra, B., Abeln, S., Meijer, G. A., & Fijneman, R. J. A. (2015). High prevalence and clinical relevance of genes affected by chromosomal breaks in colorectal cancer. PLoS One, 10(9), Article e0138141. https://doi.org/10.1371/journal.pone.0138141
van Dijk, E., Hoogeveen, A., & Abeln, S. (2015). The Hydrophobic Temperature Dependence of Amino Acids Directly Calculated from Protein Structures. PLoS Computational Biology, 11(5), Article e1004277. https://doi.org/10.1371/journal.pcbi.1004277
Bawono, P., Van Der Velde, A., Abeln, S., & Heringa, J. (2015). Quantifying the displacement of mismatches in multiple sequence alignment benchmarks. PLoS One, 10(5), Article e0127431. https://doi.org/10.1371/journal.pone.0127431
Stringer, B., Meroño-Peñuela, A., Loizou, A., Abeln, S., & Heringa, J. (2015). To SCRY Linked data: Extending SPARQL the easy way. CEUR Workshop Proceedings, 1501, 8-14.
Stringer, B., Meroño-Peñuela, A., Loizou, A., Abeln, S., & Heringa, J. (2015). SCRY: Enabling quantitative reasoning in SPARQL queries. CEUR Workshop Proceedings, 1546, 214-215.
Stringer, B., Dijkstra, M., Feenstra, A., Abeln, S., & Heringa, J. (2015). Explaining disease using big data: How valid is your pathway? In W. W. Smari, & V. Zeljkovic (Eds.), Proceedings of the 2015 International Conference on High Performance Computing and Simulation, HPCS 2015 (pp. 662-664). Article 7237114 (Proceedings of the 2015 International Conference on High Performance Computing and Simulation, HPCS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPCSim.2015.7237114
Kukic, P., Kannan, A., Dijkstra, M. J. J., Abeln, S., Camilloni, C., & Vendruscolo, M. (2015). Mapping the Protein Fold Universe Using the CamTube Force Field in Molecular Dynamics Simulations. PLoS Computational Biology, 11(10), Article e1004435. https://doi.org/10.1371/journal.pcbi.1004435
Ni, R., Kleijn, J. M., Abeln, S., Cohen Stuart, M. A., & Bolhuis, P. G. (2015). Competition between surface adsorption and folding of fibril-forming polypeptides. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 91(2), Article 022711. https://doi.org/10.1103/PhysRevE.91.022711
2014
Scholarly publications
Abeln, S., Vendruscolo, M., Dobson, C. M., & Frenkel, D. (2014). A simple lattice model that captures protein folding, aggregation and amyloid formation. PLoS One, 9(1), Article e85185. https://doi.org/10.1371/journal.pone.0085185
May, A., Pool, R., Van Dijk, E., Bijlard, J., Abeln, S., Heringa, J., & Feenstra, K. A. (2014). Coarse-grained versus atomistic simulations: Realistic interaction free energies for real proteins. Bioinformatics, 30(3), 326-334. https://doi.org/10.1093/bioinformatics/btt675
May, A., Abeln, S., Crielaard, W., Heringa, J., & Brandt, B. W. (2014). Unraveling the outcome of 16S rDNA-based taxonomy analysis through mock data and simulations. Bioinformatics, 30(11), 1530-1538. https://doi.org/10.1093/bioinformatics/btu085
2013
Scholarly publications
Abeln, S., Molenaar, D., Feenstra, K. A., Hoefsloot, H. C. J., Teusink, B., & Heringa, J. (2013). Bioinformatics and systems biology: Bridging the gap between heterogeneous student backgrounds. Briefings in Bioinformatics, 14(5), 589-598. https://doi.org/10.1093/bib/bbt023
Ni, R., Abeln, S., Schor, M., Cohen Stuart, M. A., & Bolhuis, P. G. (2013). Interplay between folding and assembly of fibril-forming polypeptides. Physical Review Letters, 111(5), Article 058101. https://doi.org/10.1103/PhysRevLett.111.058101
Edwards, H., Abeln, S., & Deane, C. M. (2013). Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies. PLoS Computational Biology, 9(11), Article e1003325. https://doi.org/10.1371/journal.pcbi.1003325
2012
Scholarly publications
Bonder, M. J., Abeln, S., Zaura, E., & Brandt, B. W. (2012). Comparing clustering and pre-processing in taxonomy analysis. Bioinformatics, 28(22), 2891-2897. https://doi.org/10.1093/bioinformatics/bts552
2011
Scholarly publications
Abeln, S., & Frenkel, D. (2011). Erratum: Correction (Biophysical Journal (2011) 100 (693-700)). Biophysical Journal, 101(4), 1014. https://doi.org/10.1016/j.bpj.2011.07.032
Abeln, S., & Frenkel, D. (2011). Accounting for protein-solvent contacts facilitates design of nonaggregating lattice proteins. Biophysical Journal, 100(3), 693-700. https://doi.org/10.1016/j.bpj.2010.11.088
2010
Scholarly publications
Pirovano, W., Abeln, S., Feenstra, K. A., & Heringa, J. (2010). Multiple alignment of transmembrane protein sequences. In Structural Bioinformatics of Membrane Proteins (pp. 103-122). Springer Vienna. https://doi.org/10.1007/978-3-7091-0045-5_6
2008
Scholarly publications
Abeln, S., & Frenkel, D. (2008). Disordered flanks prevent peptide aggregation. PLoS Computational Biology, 4(12), Article e1000241. https://doi.org/10.1371/journal.pcbi.1000241
2007
Scholarly publications
Abeln, S., Teubner, C., & Deane, C. M. (2007). Using phylogeny to improve genome-wide distant homology recognition. PLoS Computational Biology, 3(1), 73-83. https://doi.org/10.1371/journal.pcbi.0030003
2005
Scholarly publications
Abeln, S., & Deane, C. M. (2005). Fold usage on genomes and protein fold evolution. Proteins: Structure, Function and Genetics, 60(4), 690-700. https://doi.org/10.1002/prot.20506
Winstanley, H. F., Abeln, S., & Deane, C. M. (2005). How old is your fold? Bioinformatics, 21(SUPPL. 1), i449-i458. https://doi.org/10.1093/bioinformatics/bti1008