Prof. Tamar Schlick


Selected Publications:


See complete list at: Schlick Group Publications
  • G. Quarta and T. Schlick, Riboswitch Distribution in the Human Gut Microbiome Reveals Common Metabolite Pathways, J. Phys. Chem. B, https://doi.org/10.1021/acs.jpcb.4c00267, 2024.

  • T. Schlick and S. Yan, Modeling and Simulating RNA: Combining Structural, Dynamic, and Evolutionary Perspectives for Coronavirus Applications, Comprehensive Computational Chemistry, Editors: Yanez, Manuel and Boyd, Russell J., http://dx.doi.org/10.1016/B978-0-12-821978-2.00118-5, 3:886-984, 2024.

  • Z. Li and T. Schlick, Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics, Nucleic Acids Research, https://doi.org/10.1093/nar/gkad1121, 2023.

  • A. Mao, C. Chen, S. Portillo-Ledesma, and T. Schlick, Effect of Single-Residue Mutations on CTCF Binding to DNA: Insights from Molecular Dynamics Simulations, Int. J. Mol. Sci., https://doi.org/10.3390/ijms24076395, 24(7): 6395, 2023.

  • S. Portillo-Ledesma, Z. Li, and T. Schlick, Genome modeling: From chromatin fibers to genes, Curr. Opin. Struct. Biol., https://doi.org/10.1016/j.sbi.2022.102506, 78:102506, 2023.

  • S. Yan, Q. Zhu, J. Hohl, A. Dong, and T. Schlick, Evolution of coronavirus frameshifting elements: Competingstem networks explain conservation and variability, Proc. Natl. Acad. Sci., https://doi.org/10.1073/pnas.2221324120, 120(20): e2221324120, 2023.

  • Z. Li, S. Portillo-Ledesma, and T. Schlick, Brownian Dynamics Simulations of Mesoscale Chromatin Fibers, Biophys. J., https://doi.org/10.1016/j.bpj.2022.09.013, 122:1-14, 2023.

  • T. Schlick, Innovations in biophysics: A sampling of ideas celebrating Ned Seeman's legacy, Biophys. J.,https://doi.org/10.1016/j.bpj.2022.11.030, 121:E01-E02, 2022.

  • L. Rolband, D. Beasock, Y. Wang, Y. Shu, J. D. Dinman, T. Schlick, Y. Zhou, J. S. Kieft, S. Chen, G. Bussi, A. Oukhaled, X. Gao, P. Šulc, D. Binzel, A. S. Bhullar, C. Liang, P. Guo, K. A. Afonin, Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions, Computational and Structural Biotechnology Journal, https://doi.org/10.1016/j.csbj.2022.11.007, 20:6120-6137, 2022.

  • S. Portillo-Ledesma, M. Wagley and T. Schlick, Chromatin transitions triggered by LH density as epigenetic regulators of the genome, Nucleic Acids Research, https://doi.org/10.1093/nar/gkac757, 50(18):10328-10342, 2022.

  • Q. Zhu, L. Petingi, and T. Schlick, RNA-As-Graphs Motif Atlas—Dual Graph Library of RNA Modules and Viral Frameshifting-Element Applications, Int. J. Mol. Sci., https://doi.org/10.3390/ijms23169249, 23:9249, 2022.

  • S. Yan, Q. Zhu, S. Jain, and T. Schlick, Length-dependent motions of SARS-CoV-2 frameshifting RNA pseudoknot and alternative conformations suggest avenues for frameshifting suppression, Nat Commun., https://doi.org/10.1038/s41467-022-31353-w, 13(1):4284, Jul 25, 2022.

  • S. Swygert, D. Lin, S. Portillo-Ledesma, P. Lin, D. Hunt, C. Kao, T. Schlick, W. Noble, and T. Tsukiyama, Local chromatin fiber folding represses transcription and loop extrusion in quiescent cells, Elife doi.org/10.7554/eLife.72062, November 4, 2021.

  • T. Schlick, From butterflies to bits: A sweeping vision for the code of life, Biophysical Reports, doi: 10.1016/j.bpr.2021.100010, September 8, 2021.

  • T. Schlick, Isabella L. Karle: A Crystallography Pioneer, DNA AND CELL BIOLOGY, DOI: 10.1089/dna.2021.0372, Volume 40, Number 7, 2021.

  • T. Schlick, Q. Zhu, A. Dey, S. Jain, S. Yan, and A. Laederach, To Knot or Not to Knot: Multiple Conformations of the SARS-CoV‐2 Frameshifting RNA Element, Journal of the American Chemical Society, 143(30): 11404-11422, DOI: 10.1021/jacs.1c03003, 2021.

  • T. Schlick and T. C. Bishop, MGO on the go: Multiscale genome symposium - annual biophysical society meeting 2021, Biophysical Reviews, 13:309–310 (2021).

  • Tamar Schlick, Stephanie Portillo-Ledesma, Mischa Blaszczyk, Luke Dalessandro, Somnath Ghosh, Klaus Hackl, Cale Harnish, Shravan Kotha, Daniel Livescu, Arif Masud, Karel Matouš, Arturo Moyeda, Caglar Oskay, and Jacob Fish, A Multiscale Vision - Illustrative Applications From Biology to Engineering, International Journal for Multiscale Computational Engineering, 19(2):39–73 (2021).

  • Tamar Schlick, Stephanie Portillo-Ledesma, Christopher G Myers, Lauren Beljak, Justin Chen, Sami Dakhel, Daniel Darling, Sayak Ghosh, Joseph Hall, Mikaeel Jan, Emily Liang, Sera Saju, Mackenzie Vohr, Chris Wu, Yifan Xu, Eva Xue, Biomolecular Modeling and Simulation: A Prospering Multidisciplinary Field, Annu Rev Biophys, doi: 10.1146/annurev-biophys-091720-102019, 50:267-301 (2021).

  • T. Schlick and S. Portillo-Ledesma, Biomolecular modeling thrives in the age of technology, Nature Computational Sciencehttps://doi.org/10.1038/s43588-021-00060-9 (2021).

  • Pablo Aurelio Gómez-García, Stephanie Portillo-Ledesma, Maria Victoria Neguembor, Martina Pesaresi, Walaa Oweis, Talia Rohrlich, Stefan Wieser, Eran Meshorer, Tamar Schlick, Maria Pia Cosma, Melike Lakadamyali, Mesoscale Modeling and Single-Nucleosome Tracking Reveal Remodeling of Clutch Folding and Dynamics in Stem Cell Differentiation, Cell Repdoi: 10.1016/j.celrep.2020.108614, 34(2):108614 (2021).

  • T. Schlick, E. J. Sundberg, S. J. Schroeder, M. M. Babu, Biophysicists' outstanding response to Covid-19, Biophys J., doi: 10.1016/j.bpj.2021.02.020, 120(6):E1-E2 (2021).

  • Q. Zhu and T. Schlick, A Fiedler Vector Scoring Approach for Novel RNA Motif Selection, Journal of Physical Chemistry B, doi: https://doi.org/10.1021/acs.jpcb.0c10685 (2021).

  • Yusufova N, Kloetgen A, Teater M, Osunsade A, Camarillo JM, Chin CR, Doane AS, Venters BJ, Portillo-Ledesma S, Conway J, Phillip JM, Elemento O, Scott DW, Béguelin W, Licht JD, Kelleher NL, Staudt LM, Skoultchi AI, Keogh MC, Apostolou E, Mason CE, Imielinski M, Schlick T, David Y, Tsirigos A, Allis CD, Soshnev AA, Cesarman E, Melnick AM, Histone H1 loss drives lymphoma by disrupting 3D chromatin architecture, Nature 589(7841):299-305 (2021).

  • Portillo-Ledesma S, Tsao LH, Wagley M, Lakadamyali M, Cosma MP, Schlick T., Nucleosome Clutches are Regulated by Chromatin Internal Parameters, J Mol Biol. doi: 10.1016/j.jmb.2020.11.001 (2020).

  • T. Schlick, Q. Zhu, S. Jain, and S. Yan, Structure-Altering Mutations of the SARS-CoV-2Frameshifting RNA Element, Biophysical Society, doi: https://doi.org/10.1016/j.bpj.2020.10.012 (2020).

  • E. Bischof, J. A.C. Broek, C. R. Cantor, A. J. Duits, A. Ferro, H. W. Gao, Z. Li, S. L. de Maria, N. I. Maria, B. Mishra, K. I. Mishra, L. van der Ploeg, L. Rudolph, T. Schlick, & RxCOVEA Framework, ANERGYTO SYNERGY—THE ENERGY FUELING THERXCOVEA FRAMEWORK, International Journal for Multiscale Computational Engineering, 18(3): 329-333 (2020).

  • T. Schlick, Multiscale Genome Organization: Dazzling Subject and Inventive Methods, Biophysical Journal, doi: 10.1016/j.bpj.2020.04.007 (2020).

  • T. Schlick, Eight Suggestions for Future Leaders of Science and Technology, The Biophysicist, 1(1):1-5 2020.

  • T. Schlick, My blue whale: Seeking order in a chaotic world. An autobiographical reflection, Proceedings of the Seventh International Conference on Algorithms and Computational Biology (AlCoB 2020), Springer Lecture Notes in Bioinformatics (LNBIS)/Lecture Notes in Computer Science (LNCS) 12099: pages ix–xvi, C. Martin-Vide, M. A. Vega-Rodrigez, and T. Wheeler (Eds.), 2020.

  • A. Sridhar, S. E. Farr, G. Portella, T. Schlick, M. Orozco, and R. Collepardo-Guevara, Emergence of chromatin hierarchical loops from protein disorder and nucleosome asymmetry, PNAS, doi: 10.1073/pnas.1910044117 (2020).

  • S. Jain, Q. Zhu, A. S.P. Paz, and T. Schlick, Identification of novel RNA design candidates by clustering the extended RNA-As-Graphs library, Biochim Biophys Acta Gen Subj, 1864(6): 129534, doi: 10.1016/j.bbagen.2020.129534 (2020).

  • S. Jain, Y. Tao, and T. Schlick, Inverse folding with RNA-As-Graphs produces a large pool of candidate sequences with target topologies, J. Struct. Biol., 209(6): 107438, doi: 10.1016/j.jsb.2019.107438 (2020).

  • S. Portillo, T. Schlick, Bridging chromatin structure and function over a range of experimental spatial and temporal scales by molecular modeling, WIREs Computational Molecular Science, 10(2):e1434, (2019).

  • L. Petingi, T. Schlick, Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots, Algorithms for Computational Biology, 68-79, (2019).

  • C. G. Myers, D. E. Olins, A. L. Olins, and T. Schlick, Mesoscale Modeling of Nucleosome-Binding Antibody PL2-6: Mono- versus Bivalent Chromatin Complexes, Biophys. J., 118: 1-11, doi: 10.1016/j.bpj.2019.08.019 (2019).

  • G. Meng, M. Tariq, S. Jain, S. Elmetwaly, T. Schlick, RAG-Web: RNA Structure Prediction/Design using RNA-As-Graphs, Bioinformatics, doi: 10.1093/bioinformatics/btz611 (2019).

  • J. Jung, W. Nishima, M. Daniels, G. Bascom, C. Kobayashi, A. Adedoyin, M. Wall, A. Lappala, D. Phillips, W. Fischer, C. Tung, T. Schlick, Y. Sugita, K. Y. Sanbonmatsu, Scaling molecular dynamics beyond 100,000 processor cores for large-scale biophysical simulations, Journal of Computational Chemistry, 40(21): 1919-1930 (2019).

  • O. Perisic, S. Portillo-Ledesma, and T. Schlick, Sensitive effect of linker histone binding mode and subtype on chromatin condensation, Nucleic Acids Research, doi: 10.1093/nar/gkz234 (2019).

  • S. Jain, S. Saju, L. Petingi, and T. Schlick, An Extended Dual Graph Library and Partitioning Algorithm Applicable to Pseudoknotted RNA Structures, Methods, doi: 10.1016/j.ymeth.2019.03.022 (2019).

  • G. Bascom, C. Myers, and T. Schlick, Mesoscale modeling reveals formation of an epigenetically driven HOXC gene hub, PNAS, 116(11): 4955-4962 (2019).

  • S. Jain, C. S. Bayrak, L. Petingi, and T. Schlick, Dual Graph Partitioning Highlights a Small Group of Pseudoknot-Containing RNA Submotifs, Genes, 9(8): 371 (2018).

  • Swati Jain, Alain Laederach, Silvia B V. Ramos, and T. Schlick, A pipeline for computational design of novel RNA-like topologies, Nucleic Acids Res., 46(14):7040-7051, doi.org/10.1093/nar/gky524 (2018).

  • G. Bascom, and T. Schlick, Chromatin Fiber Folding Directed by Cooperative Histone Tail Acetylation and Linker Histone Binding, Biophysical Journal, 114(10): 2376-2385 (2018).

  • T. Schlick, Adventures with RNA graphs, Methods, 143: 16-33, doi: 10.1016/j.ymeth.2018.03.009 (2018).

  • G. Bascom, and T. Schlick, Mesoscale Modeling of Chromatin Fibers, Nuclear Architecture and Dynamics, 123-147 (2018).

  • S. Jain, T. Schlick, F-RAG: Generating Atomic Coordinates from RNA Graphs by Fragment Assembly, J. Mol. Biol., 429(23): 3587-3605 (2017).

  • Rao SSP, Huang SC, Glenn St Hilaire B, Engreitz JM, Perez EM, Kieffer-Kwon KR, Sanborn AL, Johnstone SE, Bascom GD, Bochkov ID, Huang X, Shamim MS, Shin J, Turner D, Ye Z, Omer AD, Robinson JT, Schlick T, Bernstein BE, Casellas R, Lander ES, Aiden EL, Cohesin Loss Eliminates All Loop Domains, Cell , 171(2): 305-320 (2017).

  • O. Perisic, and T. Schlick, Dependence of the Linker Histone and Chromatin Condensation on the Nucleosome Environment, The Journal of Physical Chemistry-B, 121(33): 7823-7832 (2017).

  • T. Schlick, and A. M. Pyle, RNA Structural Variability and Functional Versatility Challenge RNA Structural Modeling and Design, Biophysical Journal, 113(2): E1-E2 (2017).

  • G. Bascom, T. Kim, and T. Schlick, Kilobase Pair Chromatin Fiber Contacts Promoted by Living-System-Like DNA Linker Length Distributions and Nucleosome Depletion, The Journal of Physical Chemistry-B, 121(15): 3882-3894 (2017).

  • T. Schlick, and A. M. Pyle, Opportunities and Challenges in RNA Structural Modeling and Design, Biophysical Journal, 113(2): 225-234 (2017).

  • C. S. Bayrak, N. Kim, and T. Schlick, Using sequence signatures and kink-turn motifs in knowledge-based statistical potentials for RNA structure prediction, Nucleic Acids Res., 45(9): 5414-5422, doi: 10.1093/nar/gkx045 (2017).

  • G. Bascom, and T. Schlick, Linking Chromatin Fibers to Gene Folding by Hierarchical Looping, Biophysical Journal, 112(3): 434-445 (2017).

  • T. Schlick, and L. Loew, Unraveling Genome Biophysics, Biophysical Journal, 112(3): E1-E2 (2017).

  • O. Perisic, and T. Schlick, Computational strategies to address chromatin structure problems, Phys Biol., 13(3): 035006 (2016).

  • A. Luque, G. Ozer, and T. Schlick, Correlation among DNA Linker Length, Linker Histone Concentration, and Histone Tails in Chromatin, Biophysical Journal, 110(11): 2309-2319 (2016).

  • G. Bascom, K.Y. Sanbonmatsu, and T. Schlick, Mesoscale Modeling Reveals Hierarchical Looping of Chromatin Fibers Near Gene Regulatory Elements, The Journal of Physical Chemistry-B, 120(33): 8642-53, doi: 10.1021/acs.jpcb.6b03197 (2016).

  • T. Kim, B. D. Freudenthal, W. A. Beard, S. H. Wilson, and T. Schlick, Insertion of oxidized nucleotide triggers rapid DNA polymerase opening, Nucleic Acids Res., 44(9): 4409-24, doi: 10.1093/nar/gkw174 (2016).

  • A. M. Pyle, and T. Schlick, Challenges in RNA Structural Modeling and Design, J. Mol. Biol., 428(5): 733-735, doi: 10.1016/j.jmb.2016.02.012 (2016).

  • S. Grigoryev, G. Bascom, J. Buckwalter, M. Schubert, C. Wookcock, and T. Schlick, Hierarchical looping of zigzag nucleosome chains in metaphase chromosomes, PNAS, 113(5): 1238-43, doi: 10.1073/pnas.1518280113 (2016).

  • L. Hua, Y. Song, N. Kim, C. Laing, J. Wang, and T. Schlick, CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking, PLoS ONE, 11(1): e0147097, doi: 10.1371/journal.pone.0147097 (2016).

  • L. Petingi and T. Schlick, Partitioning RNAs into pseudonotted and pseudoknot-free regions modeled as Dual Graphs, q-bio.QM,arXiv, 1601.04259 (2016).

  • N. Baba, S. Elmetwaly, N. Kim, and T. Schlick, Predicting Large RNA-Like Topologies by a Knowledge-Based Clustering Approach, J. Mol. Biol., 428(5 Pt A): 811-21, doi: 10.1016/j.jmb.2015.10.009 (2016).

  • M. Zahran, C. S. Bayrak, S. Elmetwaly, and T. Schlick, RAG-3D: a search tool for RNA 3D substructures, Nucleic Acids Res., 43(19): 9474-88, doi: 10.1093/nar/gkv823 (2015).

  • R. Collepardo-Guevara , G. Portella , M. Vendruscolo , D. Frenkel , T. Schlick , and M. Orozco, Chromatin unfolding by epigenetic modifications explained by dramatic impairment of internucleosome interactions: a multiscale computational study, J. Am. Chem. Soc., 137(32): 10205-15, DOI: 10.1021/jacs.5b04086 (2015).

  • G. Ozer, A. Luque, and T. Schlick, The chromatin fiber: multiscale problems and approaches, Curr. Opin. Struct. Biol., 31: 124-139 (2015).

  • N. Kim, M. Zahran, and T. Schlick, Computational Prediction of Riboswitch Tertiary Structures Including Pseudoknots by RAGTOP: A Hierarchical Graph Sampling Approach, Methods Enzymol., 553, 115-35, DOI: 10.1016/bs.mie.2014.10.054 (2015).

  • G. Ozer, R. Collepardo-Guevara, and T. Schlick, Forced unraveling of chromatin fibers with nonuniform linker DNA lengths, J Phys Condens Matter, 27(6): 064113, DOI:10.1088/0953-8984/27/6/064113 (2015).

  • B. D. Freudenthal, W. A. Beard, L. Perera, D. D. Shock, T. Kim, T. Schlick, and S. H. Wilson, Uncovering the polymerase-induced cytotoxicity of an oxidized nucleotide, Nature, 517, 635-639, DOI:10.1038/nature13886 (2014).

  • N. Kim, Z. Zheng, S. Elmetwaly and T. Schlick, RNA Graph Partitioning for the Discovery of RNA Modularity: A Novel Application of Graph Partition Algorithm to Biology, PLoS ONE, 9(9): e106074, DOI: 10.1371/journal.pone.0106074 (2014).

  • A. Luque, R. Collepardo-Guevara, S. Grigoryev and T. Schlick, Dynamic condensation of linker histone C-terminal domain regulates chromatin structure, Nucleic Acids Res., 42(12): 7553-7560, DOI: 10.1093/nar/gku491 (2014).

  • R. Collepardo-Guevara, and T. Schlick, Chromatin fiber polymorphism triggered by variations of DNA linker lengths, PNAS, DOI: 10.1073/pnas.1315872111 (2014).

  • N. Kim, C. Laing, S. Elmetwaly, S. Jung, J. Curuksu, and T. Schlick, Graph-based sampling for approximating global helical topologies of RNA, PNAS, DOI: 10.1073/pnas.1318893111 (2014).

  • Y. Li, B. D. Freudenthal, W. A. Beard, S. H. Wilson, and T. Schlick, Optimal and Variant Metal-Ion Routes in DNA Polymerase β's Conformational Pathways, J. Am. Chem. Soc., DOI: 10.1021/ja412701f (2014).

  • S. Jung and T. Schlick, Interconversion between Parallel and Antiparallel Conformations of a 4H RNA junction in Domain 3 of Foot-and-Mouth Disease Virus IRES Captured by Dynamics Simulations, Biophys J., 106(2): 447-458, (2014).

  • B. S. Benítez, Z. R. Barbati, K. Arora, J. Bogdanovic and T. Schlick, How DNA Polymerase X Preferentially Accommodates Incoming dATP Opposite 8-Oxoguanine on the Template, Biophys J., 105(11): 2559-2568, December (2013).

  • T. Schlick, The 2013 Nobel Prize in Chemistry Celebrates Computations in Chemistry and Biology, SIAM News, 46(10), December (2013).

  • C. Laing, S. Jung, N. Kim, S. Elmetwaly, M. Zahran, and T. Schlick, Predicting Helical Topologies in RNA Junctions as Tree Graphs, PLoS ONE, 8(8): e71947, DOI:10.1371/journal.pone.0071947 (2013).

  • Y. Li, and T. Schlick, "Gate-keeper" Residues and Active-Site Rearrangements in DNA Polymerase μ Help Discriminate Non-cognate Nucleotides, PLoS Comput. Biol., 9(5), DOI:10.1371/journal.pcbi.1003074 (2013).

  • R. Collepardo-Guevara, and T. Schlick, Insights into chromatin fibre structure by in vitro and in silico single-molecule stretching experiments, Biochem. Soc. Trans., 41(2): 494-500 (2013).

  • S. Jung, and T. Schlick, Candidate RNA structures for domain 3 of the foot-and-mouth-disease virus internal ribosome entry site, Nucleic Acids Res., 41(3): 1483-95 (2013).

  • N. Kim, L. Petingi, and T. Schlick, Network Theory Tools for RNA Modeling, WSEAS Transactions on Math, 12(9): 941-955 (2013).

  • N. Kim, N. Fuhr and T. Schlick, Graph Applications to RNA Structure and Function, Chapter 3, pp. 23–51, In Biophysics of RNA Folding, Ed. R. Russel, Biophysics for the Life Sciences 3, Springer Verlag (2013).

  • R. Collepardo-Guevara and T. Schlick, Crucial role of dynamic linker histone binding and divalent ions for DNA accessibility and gene regulation revealed by mesoscale modeling of oligonucleosomes, Nucleic Acids Research, DOI:10.1093/nar/gks600 (2012).

  • T. Schlick, K. Arora, W. A. Beard, and S. H. Wilson, Perspective: pre-chemistry conformational changes in DNA polymerase mechanisms, Theor Chem Acc, 131(12): 1287 (2012).

  • N. Kim and T. Schlick, A New Toolkit for Modeling RNA from a Pseudo-Torsional Space, J. Mol. Biol., 421(1): 1-5 (2012).

  • Y. Li, C. L. Gridley, J. Jaeger, J. B. Sweasy, and T. Schlick, Unfavorable electrostatic and steric interactions in DNA polymerase beta E295K mutant interfere with the enzyme's pathway, J. Am. Chem. Soc., 134(24): 9999-10010 (2012).

  • Innovations in Biomolecular Modeling and Simulations, Volume 2, T. Schlick ed., The Royal Society of Chemistry, ISBN: 978-1-84973-505-6, DOI:10.1039/9781849735056 (2012).

  • Innovations in Biomolecular Modeling and Simulations, Volume 1, T. Schlick ed., The Royal Society of Chemistry, ISBN: 978-1-84973-504-9, DOI:10.1039/9781849735049 (2012).

  • T. Schlick, J. Hayes, and S. Grigoryev, Toward Convergence of Experimental Studies and Theoretical Modeling of the Chromatin Fiber, JBC, 287: 5183-5191 (2012).

  • G. Quarta, K. Sin and T. Schlick, Dynamic Energy Landscapes of Riboswitches Help Interpret Conformational Rearrangements and Function, PLoS Comput Biol, 8(2): e1002368. doi:10.1371/journal.pcbi.1002368 (2012).

  • R. Collepardo-Guevara and T. Schlick, The Effect of Linker Histone's Nucleosome Binding Affinity on Chromatin Unfolding Mechanisms, Biophys. J., 111(7):1670-1680 (2011).

  • C. Laing, D. Wen, J. Wang and T. Schlick, Predicting coaxial helical stacking in RNA junctions, Nucleic Acids Research, doi:10.1093/nar/gkr629 (2011).

  • J. Izzo, N. Kim, S. Elmetwaly and T. Schlick, RAG: an update to RNA-As-Graphs resource, BMC Bioinformatics, 12: 219 (2011).

  • C. Laing and T. Schlick, Computational approaches to RNA structure prediction, analysis, and design, Curr. Opin. Struct. Biol., 21: 1-13 (2011).

  • L. Yunlang and T. Schlick, Modeling DNA Polymerase μ Motions: Subtle Transitions before Chemistry, Biophys. J., 99(10): 3463-3472 (2010).

  • T. Schlick, Molecular Modeling: An Interdisciplinary Guide, Second Edition, Springer-Verlag, NY (2010).

  • H. H. Gan and T. Schlick, Chromatin Ionic Atmosphere Analyzed by a Mesoscale Electrostatic Approach, Biophys. J., 99(8): 2587-2596 (2010).

  • T. Schlick, R. Collepardo-Guevara, L. A. Halvorsen, S. Jung and X. Xiao, Biomolecular Modeling and Simulation: A Field Coming of Age, Quart. Rev. Biophys., 44(2): 191-228 (2011).

  • M. Foley, V. Padow and T. Schlick, Extraordinary Ability of DNA Pol λ to Stabilize Misaligned DNA, J. Am. Chem. Soc., 132: 13403-13416 (2010).

  • O. Perisic, R. Collepardo-Guevara and T. Schlick, Modeling Studies of Chromatin Fiber Structure as a Function of DNA Linker Length, J. Mol. Biol., 403: 777-802 (2010).

  • C. Laing and T. Schlick, Computational approaches to RNA 3D modeling, J. Phys.: Condens. Matter, 22: 283101 (2010).

  • N. Kim, J. A. Izzo, S. Elmetwaly, H. H. Gan and T. Schlick, Computational Generation and Screening of RNA Motifs in Large Nucleotide Sequence Pools, Nuc. Acids Res., doi:10.1093/nar/gkq282 (2010).

  • T. Schlick, Mathematical and Biological Scientists Assess the State-of-the-Art in RNA Science at an IMA Workshop, Intl. J. Mult. Sci. Eng., 8 (4): 369-378 (2010).

  • T. Schlick and O. Perisic, Meoscale Simulations of Two Nucleosome-Repeat Length Oligonucleosomes, Phys. Chem. Chem. Phys., 11: 10729-10737 (2009).

  • G. Quarta, N. Kim, J. A. Izzo, and T. Schlick, Analysis of Riboswitch Structure and Function by an Energy Landscape Framework, J. Mol. biol., 393: 993-1003 (2009).

  • K. Arora and T. Schlick, Conformational Transitions in DNA Polymerases, VDM Verlag, Berlin (2009).

  • C. Laing and T. Schlick, Analysis of Four-Way Junctions in RNA Structures, J. Mol. Biol. 390: 547-559 (2009).

  • S. Grigoryev, G. Arya, S. Correll, C. Woodcock and T. Schlick, Evidence for Heteromorphic Chromatin Fibers From Analysis of Nucleosome Interactions, Proc. Natl. Acad. Sci. USA, 106: 13317-13322 (2009).

  • T. Schlick, From Macroscopic to Mesoscopic Models of Chromatin Folding, Chapter 15, pp. 514-535, In Bridging the Scales in Science and Engineering, J. Fish, Editor, Oxford University Press (2009).

  • T. Schlick, Molecular Dynamics-based Approaches for Enhanced Sampling of Long-time, Large-Scale Conformational Changes in Biomolecules, F1000 Biology Reports, 1-51(2009).

  • M. C. Foley and T. Schlick, Relationship Between Conformational Changes in Pol λ's Active Site Upon Binding Incorrect Nucleotides and Mismatch Incorporation Rates, J. Phys. Chem. B, 113 (39): 13035-13047 (2009).

  • T. Schlick, Monte Carlo, harmonic approximation, and coarse-graining approaches for enhanced sampling of biomolecular structure, F1000 Biology Reports, 1-48(2009).

  • G. Arya and T. Schlick, A Tale of Tails: How Histone Tails Mediate Chromatin Compaction in Different Salt and Linker Histone Environments, J. Phys. Chem. A, 16, 4045-4059 (2009).

  • B. A. Sampoli Benitez, K. Arora, L. Balistreri, and T. Schlick, Mismatched base-pair simulations for ASFV Pol X/DNA complexes help interpret frequent G*G misincorporation, J. Mol. Biol., 384, 1086-1097 (2008).

  • Y. Wang and T. Schlick, Quantum mechanics/molecular mechanics investigation of the chemical reaction in Dpo4 reveals water-dependent pathways and requirements for active site reorganization, J. Am. Chem. Soc.,130, 13240-13250 (2008).

  • M.C. Foley and T. Schlick, Simulations of DNA pol λ R517 mutants indicate 517's crucial role in ternary complex stability and suggest DNA slippage origin, J. Am. Chem. Soc., 130, 3967-3977 (2008).

  • K. Bebenek, M. Garcia-Diaz, M.C. Foley, L.C. Pedersen, T. Schlick, and T.A. Kunkel, Substrate-induced DNA strand misalignment during catalytic cycling by DNA polymerase λ, EMBO Rep., 9, 459-64 (2008).

  • Y. Xin, G. Quarta, H.H. Gan, and T. Schlick, Estimating the fraction of noncoding RNAs in mammalian transcriptomes, Bioinformatics and Biology Insights, 2, 77-95 (2008).

  • N. Kim, J.S. Shin, S. Elmetwaly, H.H. Gan, and T. Schlick, RAGPOOLS: RNA-As-Graph-Pools - A web server for assisting the design of structured RNA pools for in vitro selection, Bioinformatics, 23, 2959-2960 (2007).

  • N. Kim, H.H. Gan and T. Schlick, A computational proposal for designing structured RNA pools for in vitro selection of RNAs, RNA, 13:478-492 (2007).

  • G. Arya and T. Schlick, Efficient Global Biopolymer Sampling with End-Transfer Configurational Bias Monte Carlo, J. Chem. Phys, 126:044107 (2007).

  • Y. Wang and T. Schlick, Distinct Energetics and Closing Pathwasys for DNA Polymerase Beta with 8-oxoG Template and Different Incoming Nucleotides, BMC Structural Biology, 7:7 (2007).

  • R. Radhakrishnan and T. Schlick, Correct and Incorrect Nucleotide Incorporation Pathways in DNA Polymerase Beta, BBRC, 350: 521--529 (2006).

  • R. Radhakrishnan, K. Arora, Y. Wang, W. Beard, S. Wilson, and T. Schlick, Regulation of DNA Repair Fidelity by Molecular Checkpoints: "Gates" in DNA Polymerase Beta's Substrate Selection, Biochem., 45: 15142--15156 (2006).

  • G. Arya and T. Schlick, Role of Histone Tails in Chromatin Folding Revealed by a New Mesoscopic Oligonucleosome Model, Proc. Natl. Acad. Sci., 103: 16236--16241 (2006).

  • Y. Wang, S. Reddy, W. Beard, S. Wilson, and T. Schlick, Differing Conformational Pathways Before and After Chemistry for Insertion of dATP vs. dCTP Opposite 8-oxoG in DNA Polymerase Beta, In Press (2006).

  • T. Schlick, RNA --- The Cousin Left Behind Becomes a Star, in Computational Studies of DNA and RNA, J. Sponer and F. Lankas, Editors, in Challenges and Advances in Computational Chemistry and Physics, Vol. 2 (ISBN-10: 1-4020-4794-0), Springer- Dordrecht, The Netherlands (2006).

  • M. Foley, K. Arora, and T. Schlick, Sequential Side-Chain Residue Motions Transform the Binary into the Ternary State of DNA Polymerase λ, Biophys. J., 91: 3182--3195 (2006).

  • G. Arya, Q. Zhang, and T. Schlick, Flexible Histone Tails in a New Mesoscopic Oligonucleosome Model, Biophys. J., 91: 133--150 (2006). [Figure featured on journal cover].

  • Q. Zhang and T. Schlick, Stereochemistry and Position-Dependent Effects of Carcinogens on TATA/TBP Binding, Biophys. J., 90: 1865--1877 (2006).

  • Y. Wang, K. Arora, and T. Schlick, Subtle but Variable Conformational Rearrangements in the Replication Cycle of Sulfolobus solfataricus P2 DNA Polymerase IV May Accommodate Lesion Bypass, Prot. Sci., 15: 135--151 (2006).

  • B. A. Sampoli Benitez, K. Arora, and T. Schlick, Induced-Fit Mechanism for the Interaction of the African Swine Fever Virus DNA Polymerase X with Its Target DNA, Biophys. J., 90: 42--56 (2006). [Figure featured on journal cover].

  • U. Laserson, H. H. Gan and T. Schlick, Predicting Candidate Genomic Sequences that Correspond to Synthetic Functional RNA Motifs, Nuc. Acids Res. 33: 6057--6069 (2005).

  • U. Laserson, H. H. Gan, and T. Schlick, Exploring the Connection Between Synthetic and Natural RNAs in Genomes Via a Novel Computational Approach, in New Algorithms for Macromolecular Simulation, Proceedings of the Fourth International Workshop on Algorithms for Macromolecular Modelling, Leicester, UK, August 2004'', B. Leimkuhler, C. Chipot, R. Elber, A. Laaksonen, A. Mark, T. Schlick, C. Schuette, R.D. Skeel, Editors, Lecture Notes in Computational Science and Engineering, Vol. 49 (ISBN 3­540­25542­7), Springer­-Verlag, Berlin (2005).

  • R. Radhakrishnan and T. Schlick, Fidelity Discrimination in DNA Polymerase β: Differing Closing Profiles for a Mismatched (G:A) Versus Matched (G:C) Base Pair, J. Amer. Chem. Soc. 127: 13245--13252 (2005).

  • K. Arora, W. A. Beard, S. H. Wilson, and T. Schlick, Mismatch Induced Conformational Distortions in Polymerase β Support an Induced­Fit Mechanism for Fidelity, Biochem. 44: 13328--13341 (2005).

  • J. Gevertz, H. H. Gan, and T. Schlick, In Vitro RNA Random Pools are Not Structurally Diverse: A Computational Analysis, RNA 11: 853--863 (2005).

  • J. Sun, Q. Zhang, and T. Schlick, Electrostatic Mechanism of Nucleosomal Array Folding Revealed by Computer Simulation, Proc. Natl. Acad. Sci. 102: 8180--8185 (2005).

  • K. Arora and T. Schlick, Conformational Transition Pathway of Polymerase β/DNA upon Binding Correct Incoming Substrate, J. Phys. Chem. B 109: 5358--5367 (2005).

  • T. Schlick, The Critical Collaboration Between Art and Science: Applying An Experiment on a Bird in an Air Pump to the Ramifications of Genomics on Society, Leonardo 38(4): 323--329 (2005).

  • S. Pasquali, H. H. Gan and T. Schlick, Modular RNA Architecture Revealed by Computational Analaysis of Existing Pseudoknots and Ribosomal RNAs, Nuc. Acids Res. 33: 1384--1398 (2005).

  • D. Fera, N. Kim, N. Shiffeldrim, J. Zorn, U. Laserson, H.H. Gan, and T. Schlick, RAG: RNA-As-Graphs Web Resource, BMC Bioinformatics 5: 88--97 (2004). (http://www.biomedcentral.com/1471­2105/5/88).

  • K. Arora and T. Schlick, In Silico Evidence for DNA Polymerase β's Substrate-Induced Conformational Change, Biophys. J. 87: 3088--3099 (2004).

  • Q. Zhang, S. Broyde, and T. Schlick, Deformations of Promoter DNA Bound to Carcinogens Help Interpret Effects on TATA-Element Structure and Activity, Phil. Trans. Royal Soc. Lond., Series A: Mathematical, Physical & Engineering Sciences 362: 1479--1496 (Special Volume on Mechanics of DNA) (2004).

  • R. Radhakrishnan and T. Schlick, Biomolecular Free Energy Profiles by a Shooting/Umbrella Sampling Protocol, "BOLAS", J. Chem. Phys. 121: 2436--2444 (2004).

  • L. Yang, W. A. Beard, S. H. Wilson, S. Broyde, and T. Schlick, Highly Organized but Pliant Active Site of DNA Polymerase β: Compensatory Mechanisms in Mutant Enzymes Revealed by Dynamics Simulations and Energy Analyses, Biophys. J. 86: 3392--3408 (2004).

  • J. Zorn, H. H. Gan, N. Shiffeldrim, and T. Schlick, Structural Motifs in Ribosomal RNAs: Implications for RNA Design and Genomics, Biopolymers 73: 340--347 (2004).

  • N. Kim, N. Shiffeldrim, H. H. Gan, and T. Schlick, Candidates for Novel RNA Topologies, J. Mol. Biol. 341: 1129--1144 (2004).

  • L. Yang, K. Arora, W. A. Beard, S. H. Wilson, and T. Schlick, The Critical Role of Magnesium Ions in DNA Polymerase Beta's Closing and Active Site Assembly, J. Amer. Chem. Soc. 126: 8441--8453 (2004).

  • U. Laserson, H. H. Gan, and T. Schlick, Searching for 2D RNA Geometries in Bacterial Genomes, Proceedings of the Twentieth Annual ACM Symposium on Computational Geometry, June 9--11, New York, pp. 373--377, ACM Press (2004) (http://doi.acm.org/10.1145/997817.997819).

  • H. H. Gan, D. Fera, J. Zorn, M. Tang, N. Shiffeldrim, U. Laserson, N. Kim, and T. Schlick, RAG: RNA-As-Graphs Database -- Concepts, Analysis, and Features, Bioinformatics 20: 1285--1291 (2004).

  • R. Radhakrishnan and T. Schlick, Orchestration of Cooperative Events in DNA Synthesis and Repair Mechanism Unraveled by Transition Path Sampling of DNA Polymerase β's Closing, Proc. Natl. Acad. Sci. USA 101: 5970--5975 (2004).

  • T. Schlick, Engineering Teams Up with Computer-Simulation and Visualization Tools to Probe Biomolecular Mechanisms, Biophys. J. 85: 1--4 (Invited New & Notable article) (2003). [Figure featured on journal cover].

  • J. Huang, Q. Zhang, and T. Schlick, Effect of DNA Superhelicity and Bound Proteins on Mechanistic Aspects of the Hin-mediated and Fis-enhanced Inversion, Biophys. J. 85: 804--817 (2003).

  • H. H. Gan, S. Pasquali, and T. Schlick, A Survey of Existing RNAs Using Graph Theory with Implications to RNA Analysis and Design, Nuc. Acids. Res. 31: 2926--2943 (2003).

  • L. Yang, W. A. Beard, S. H. Wilson, B. Roux, S. Broyde, and T. Schlick, Local Deformations Revealed by Dynamics Simulations of DNA Polymerase β with DNA Mismatches at the Primer Terminus, J. Mol. Biol. 321: 459--478 (2002).

  • X. Qian and T. Schlick, Efficient Multiple Timestep Integrators with Distance-Based Force Splitting for Particle-Mesh Ewald Molecular Dynamics Simulations, J. Chem. Phys. 116: 5971--5983 (2002).

  • L. Yang, W. A. Beard, S. H. Wilson, S. Broyde, and T. Schlick, Polymerase β Simulations Reveal that Arg258 Rotation is a Slow Step Rather than Large Subdomain Motions Per Se, J. Mol. Biol. 317: 651--671 (2002).

  • P. F. Batcho, D. A. Case, and T. Schlick, Optimized Particle-Mesh Ewald/Multiple-Timestep Integration for Molecular Dynamics Simulations, J. Chem. Phys. 115: 4003--4018 (2001).

  • X. Qian, D. Strahs, and T. Schlick, A New Program for Optimizing Periodic Boundary Models of Solvated Biomolecules (PBCAID), J. Comp. Chem. 22: 1843--1850 (2001).

  • X. Qian, D. Strahs, and T. Schlick, Dynamic Simulations of 13 TATA Variants Refine Kinetic Hypotheses of Sequence/Activity Relationships, J. Mol. Biol. 308: 681--703 (2001).

  • D. Beard and T. Schlick, Computational Modeling Predicts the Structure and Dynamics of the Chromatin Fiber, Structure 9: 105--114 (2001).

  • D. Beard and T. Schlick, Modeling Salt-Mediated Electrostatics of Macromolecules: The Algorithm DiSCO (Discrete Surface Charge Optimization) and Its Application to the Nucleosome, Biopolymers 58: 106--115 (2001). [Figure featured on journal cover].

  • T. Schlick, D. Beard, J. Huang, D. Strahs, and X. Qian, Computational Challenges in Simulating Large DNA Over Long Times, IEEE Comp. Sci. Eng. (Special Issue on Computational Chemistry) 2: 38--51 (2000).

  • D. Beard and T. Schlick, Inertial Stochastic Dynamics: I. Long-Timestep Methods for Langevin Dynamics, J. Chem. Phys. 112: 7313--7322 (2000).

  • T. Schlick, R.D. Skeel, A.T. Brunger, L.V. Kale, J. Hermans, K. Schulten, and J.A. Board, Jr., Algorithmic Challenges in Computational Molecular Biophysics, J. Comp. Phys. 151: 9--48 (1999).

  • T. Schlick, Computational Molecular Biophysics Today: A Confluence of Methodological Advances and Complex Biomolecular Applications, J. Comp. Phys. 151: 1--8 (1999).

  • D. Xie and T. Schlick, Effiecient Implementation of the Truncated Newton Method for Large Scale Chemistry Applications, SIAM J. Opt. 10: 132--154 (1999).

  • H. Jian, T. Schlick, and A. Vologodskii, Internal Motion of Supercoiled DNA: Brownian Dynamics Simulations of Site Juxtaposition, J. Mol. Biol. 284: 287--296 (1998). [Figure featured on journal cover].

  • T. Schlick, M. Mandziuk, R. Skeel, K. Srinivas, Nonlinear Resonance Artifacts in Molecular Dynamics, J. Comp. Phys. 139: 1--29 (1998).

  • E. Barth and T. Schlick, Overcoming Stability Limitations in Biomolecular Dynamics: I. Combining Force Splitting via Extrapolation with Langevin Dynamics in LN, J. Chem. Phys. 109: 1617--1632 (1998).

  • P. Derreumaux and T. Schlick, Simulation of the Loop Opening/Closing of the Enzyme Triosephosphate Isomerase (TIM), Biophys. J. 74: 72--81 (1998).

  • T. Schlick, Geometry Optimization, Contributed chapter to the Encyclopedia of Computational Chemistry (5 volumes), P. von Rague Schleyer, Editor in Chief, and N. L. Allinger, T. Clark, J. Gasteiger, P. A. Kollman, and H. F. Schaefer III, eds., John Wiley & Sons, West Sussex, Vol. 2, pp. 1136--1157 (1998).

  • T. Schlick, E. Barth, and M. Mandziuk, Biomolecular Dynamics at Long Timesteps: Bridging the Time Scale Gap Between Simulation and Experimentation, Annu. Rev. Biophys. Biomol. Struct. 26: 179--220 (1997).

  • R. D. Skeel, G. Zhang, and T. Schlick, A Family of Symplectic Integrators: Stability, Accuracy, and Molecular Dynamics Applications, SIAM J. Sci. Comp. 18: 203--222 (1997).

  • T. Pinou, T. Schlick, B. Li, and H. Dowling, Addition of Darwin's Third Dimension to Evolutionary Trees, J. Theor. Bio. 219: 505--512 (1996).

  • T. Schlick and A. Brandt, A Multigrid Tutorial with Applications to Molecular Dynamics, IEEE Comp. Sci. Eng. 3: 78--83 (1996).

  • B. Mishra and T. Schlick, The Notion of Error in Langevin Dynamics: (1) Linear Analysis, J. Chem. Phys. 105: 299--318 (1996).

  • T. Schlick, Pursuing Laplace's Vision On Modern Computers, Proceedings of the IMA Program in Mathematical Biology, IMA Volumes in Mathematics and its Applications, Vol. 82, pp. 219--247, J. Mesirov, K. Schulten, and D.W. Sumners, eds., Springer-Verlag, New York (1996).

  • T. Schlick, Modeling Superhelical DNA: Recent Analytical and Dynamic Approaches, Curr. Opin. Struc. Bio. 5: 245--262 (1995). Special issue on Theory and Simulation, B. Honig, ed.

  • M. Mandziuk and T. Schlick, Resonance in the Dynamics of Chemical Systems Simulated by the Implicit Midpoint Scheme, Chem. Phys. Lett. 237: 525--535 (1995).

  • G. Ramachandran and T. Schlick, Solvent Effects on Supercoiled DNA Explored by Langevin Dynamics Simulations, Phys. Rev. E 51: 6188--6203 (1995).

  • T. Schlick, B. Li, and W.K. Olson, The Effects of Salt on Supercoiled DNA Energetics and Dynamics, Biophys. J. 67: 2146--2166 (1994).

  • G. Zhang and T. Schlick, The Langevin/Implicit-Euler/Normal-Mode Scheme (LIN) for Molecular Dynamics at Large Timesteps, J. Chem. Phys. 101: 4995--5012 (1994).

  • P. Derreumaux, G. Zhang, B. Brooks, and T. Schlick, A Truncated-Newton Method Adapted for CHARMM and Biomolecular Applications, J. Comp. Chem. 15: 532--552 (1994).

  • G. Zhang and T. Schlick, LIN: A New Algorithm Combining Implicit Integration and Normal Mode Techniques for Molecular Dynamics, J. Comp. Chem. 14: 1212--1233 (1993).

  • X. Zou, I.M. Navon, M. Berger, P.K.H. Phua, T. Schlick, and F.X. Le Dimet, Numerical Experience with Limited-Memory and Truncated Newton Methods, SIAM J. Opt. 3: 582--608 (1993).

  • T. Schlick, Modified Cholesky Factorizations for Sparse Preconditioners, SIAM J. Sci. Comp. 14: 424--445 (1993).

  • T. Schlick, Optimization Methods in Computational Chemistry, in Reviews in Computational Chemistry, Volume 3, Chapter 1, pp. 1--71, K.B. Lipkowitz and D.B. Boyd, eds., VCH Publishers, New York (1992).

  • A. Nyberg and T. Schlick, On Increasing the Time Step in Molecular Dynamics, Chem. Phys. Lett. 198: 538--546 (1992).

  • T. Schlick and W.K. Olson, Trefoil Knotting Revealed by Molecular Dynamics of Supercoiled DNA, Science 257: 1110--1115 (1992).

  • T. Schlick and A. Fogelson, TNPACK -- A Truncated Newton Minimization Package for Large-Scale Problems: I. Algorithm and Usage, ACM Trans. Math. Softw. 18: 46--70 (1992).

  • T. Schlick and A. Fogelson, TNPACK -- A Truncated Newton Minimization Package for Large-Scale Problems: II. Implementation Examples, ACM Trans. Math. Softw. 18: 71--111 (1992).

  • T. Schlick and W.K. Olson, Computer Simulations of Supercoiled DNA Energetics and Dynamics, J. Mol. Biol 223: 1089-1119 (1992).

  • T. Schlick and C.S. Peskin, Can Classical Equations Simulate Quantum-Mechanical Behavior? A Molecular Dynamics Investigation of a Diatomic Molecule with a Morse Potential, Comm. Pure Appl. Math. 42: 1141--1163 (1989).

  • C.S. Peskin and T. Schlick, Molecular Dynamics by the Backward-Euler Method, Comm. Pure Appl. Math. 42: 1001--1031 (1989).

  • T. Schlick and M. Overton, A Powerful Truncated Newton Method for Potential Energy Minimization, J. Comp. Chem. 8: 1025--1039 (1987).

  • W.L. Hase, D.M. Ludlow, R.J. Wolf, and T. Schlick, Translational and Vibrational Energy Dependence of the Cross Section for H + C2H4 ---> C2H5, J. Phys. Chem. 85: 958--968 (1981).