Emil Alexov to Computational Biology
This is a "connection" page, showing publications Emil Alexov has written about Computational Biology.
Connection Strength
6.122
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Predicting protein-DNA binding free energy change upon missense mutations using modified MM/PBSA approach: SAMPDI webserver. Bioinformatics. 2018 03 01; 34(5):779-786.
Score: 0.541
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Computational Investigation of the Missense Mutations in DHCR7 Gene Associated with Smith-Lemli-Opitz Syndrome. Int J Mol Sci. 2018 Jan 04; 19(1).
Score: 0.535
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DelPhiForce web server: electrostatic forces and energy calculations and visualization. Bioinformatics. 2017 Nov 15; 33(22):3661-3663.
Score: 0.530
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Multiscale method for modeling binding phenomena involving large objects: application to kinesin motor domains motion along microtubules. Sci Rep. 2016 Mar 18; 6:23249.
Score: 0.472
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ProBLM web server: protein and membrane placement and orientation package. Comput Math Methods Med. 2014; 2014:838259.
Score: 0.420
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Protein Nano-Object Integrator (ProNOI) for generating atomic style objects for molecular modeling. BMC Struct Biol. 2012 Dec 05; 12:31.
Score: 0.376
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Predicting nonspecific ion binding using DelPhi. Biophys J. 2012 Jun 20; 102(12):2885-93.
Score: 0.364
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Highly efficient and exact method for parallelization of grid-based algorithms and its implementation in DelPhi. J Comput Chem. 2012 Sep 15; 33(24):1960-6.
Score: 0.363
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In silico and in vitro investigations of the mutability of disease-causing missense mutation sites in spermine synthase. PLoS One. 2011; 6(5):e20373.
Score: 0.338
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Computational analysis of missense mutations causing Snyder-Robinson syndrome. Hum Mutat. 2010 Sep; 31(9):1043-9.
Score: 0.322
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Homology-based modeling of 3D structures of protein-protein complexes using alignments of modified sequence profiles. Int J Biol Macromol. 2008 Aug 15; 43(2):198-208.
Score: 0.275
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Assessing the quality of the homology-modeled 3D structures from electrostatic standpoint: test on bacterial nucleoside monophosphate kinase families. J Bioinform Comput Biol. 2007 Jun; 5(3):693-715.
Score: 0.257
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Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives. BMC Bioinformatics. 2006 Nov 16; 7:503.
Score: 0.247
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Role of the protein side-chain fluctuations on the strength of pair-wise electrostatic interactions: comparing experimental with computed pK(a)s. Proteins. 2003 Jan 01; 50(1):94-103.
Score: 0.189
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E-hooks provide guidance and a soft landing for the microtubule binding domain of dynein. Sci Rep. 2018 09 05; 8(1):13266.
Score: 0.140
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DelPhiForce, a tool for electrostatic force calculations: Applications to macromolecular binding. J Comput Chem. 2017 04 05; 38(9):584-593.
Score: 0.125
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On human disease-causing amino acid variants: statistical study of sequence and structural patterns. Hum Mutat. 2015 May; 36(5):524-534.
Score: 0.111
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Structural, Dynamical, and Energetical Consequences of Rett Syndrome Mutation R133C in MeCP2. Comput Math Methods Med. 2015; 2015:746157.
Score: 0.111
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A rational free energy-based approach to understanding and targeting disease-causing missense mutations. J Am Med Inform Assoc. 2013 Jul-Aug; 20(4):643-51.
Score: 0.095
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DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocol. Bioinformatics. 2012 Jun 15; 28(12):1655-7.
Score: 0.090
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Progress in the prediction of pKa values in proteins. Proteins. 2011 Dec; 79(12):3260-75.
Score: 0.087
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On the role of electrostatics in protein-protein interactions. Phys Biol. 2011 Jun; 8(3):035001.
Score: 0.084
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ZC4H2, an XLID gene, is required for the generation of a specific subset of CNS interneurons. Hum Mol Genet. 2015 Sep 01; 24(17):4848-61.
Score: 0.028
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Structural assessment of the effects of amino acid substitutions on protein stability and protein protein interaction. Int J Comput Biol Drug Des. 2010; 3(4):334-49.
Score: 0.021