Amarda Shehu: Publications

J45: David Morrisg, Tatiana Maximovap, Erion Plaku, and Amarda Shehu*. Attenuating Dependence on Structural Data in Computing Protein Energy Landscapes. BMC Bioinformatics, 2018, in press.

J44: Wanli Qiao, Nasrin Akhterg, Xiaowen Fangu, Tatiana Maximovap, Erion Plaku, and Amarda Shehu*. From Mutations to Mechanisms and Dysfunction via Computation and Mining of Protein Energy Landscapes. BMC Genomics 19 (Suppl7):671, 2018.

J43: Nasrin Akhterg, Wanli Qiao, and Amarda Shehu*. An Energy Landscape Treatment of Decoy Selection in Template-free Protein Structure Prediction. Computation 6(2), 39, 2018 (invited to special issue on "Computation in Molecular Modeling").

J42: Daniel Veltri, Uday Kamath, and Amarda Shehu*. Deep Learning Improves Antimicrobial Peptide Recognition. Bioinformatics 34(16):2740–2747, 2018.

J41: Nasrin Akhterg and Amarda Shehu*. From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-free Protein Structure Prediction. Molecules 23(1), 216, 2018.

J40: Tatiana Maximovap, Zijing Zhang, Daniel B Carr, Erion Plaku, and Amarda Shehu*. Sample-based Models of Protein Energy Landscapes and Slow Structural Rearrangements. J Comput Biol (JCB), 25(1):33-50, 2017.

J39: Emmanuel Sapinp, Kenneth De Jong*, and Amarda Shehu*. From Optimization to Mapping: An Evolutionary Algorithm for Protein Energy Landscapes. IEEE/ACM Trans Comp Biol and Bioinf (TCBB) 15(3):719 - 731, 2018.

J38: Tatiana Maximovap, Erion Plaku*, and Amarda Shehu*. Structure-guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm. IEEE/ACM Trans Comp Biol and Bioinf (TCBB)15:(6), 1783-1796, 2018 (online pre-print since 2017).

J37: Daniel Veltrig, Uday Kamath, and Amarda Shehu*. Improving Recognition of Antimicrobial Peptides and Target Selectivity through Machine Learning and Genetic Programming. IEEE/ACM Trans Comp Biol and Bioinf (TCBB), 14(2): 300-313, 2017.

Book chapters

B6: Nasrin Akhter, Liban Hassan, Zahra Rajabi, Daniel Barbara, and Amarda Shehu. Learning Organizations of Protein Energy Landscapes: An Application on Decoy Selection in Template-Free Protein Structure Prediction. In Methods in Molecular Biology: Protein Supersecondary Structure (Springer), first edition, (Editor: Kister, A.),2018.

B5: Uday Kamath, Carlotta Domeniconi, Amarda Shehu, and Kenneth De Jong. EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications. In Intelligent Systems Reference Library: Innovations in Big Data Mining and Embedded Knowledge (Springer), first edition, (Editor: Anna Esposito, Antonietta M. Esposito, and Lakhmi C. Jain),2018.

Publications since 2011 before joining the CSM

J36: Amarda Shehu* and Erion Plaku*. A Survey of Computational Treatments of Biomolecules by Robotics-inspired Methods Modeling Equilibrium Structure and Dynamics. J Artif Intel Res (JAIR) 57:509-572, 2016.

J35: Emmanuel Sapinp, Daniel B Carr, Kenneth A De Jong*, and Amarda Shehu*. Computing energy landscape maps and structural excursions of proteins. BMC Genomics 17(Suppl 4):546, 2016.

J34: Kevin Molloyg, Rudy Clauseng, and Amarda Shehu*. A Stochastic Roadmap Method to Model Protein Structural Transitions. Robotica 34(08):1705-1733, 2016 (featured on issue cover).

J33: Kevin Molloyg and Amarda Shehu*. A General, Adaptive, Roadmap-based Algorithm for Protein Motion Computation. IEEE Trans NanoBioScience (TNB) 15(2): 158-165, 2016.

J32: Tatiana Maximovap, Ryan Moffattg, Buyong Ma, Ruth Nussinov*, and Amarda Shehu*. Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics. PLoS Comp Biol 12(4): e1004619, 2016, (top 50 most downloaded in 2016 and featured on April issue front cover. Also featured in the PLoS Comp Biol blog.)

J31: Amarda Shehu* and Ruth Nussinov*. Computational Methods for Exploration and Analysis of Macromolecular Structure and Dynamics. PLoS Comput Biol (PCB) 11(10): e1004585, 2015 (editorial).

J30: Didier Devaurs, Kevin Molloy, Marc Vaisset, Amarda Shehu, Thierry Simeon, and Juan Cortes*. Characterizing Energy Landscapes of Peptides using a Combination of Stochastic Algorithms. IEEE Trans NanoBioScience (TNB), 14(5): 545-552, 2015.

J29: Irina Hashmig and Amarda Shehu*. idDock+:Integrating Machine Learning in Probabilistic Search for Protein-protein Docking. J Computational Biology (JCB), 22(9):806-822, 2015.

J28: Rudy Clauseng and Amarda Shehu*. A Data-driven Evolutionary Algorithm for Mapping Multi-basin Protein Energy Landscapes. J Computational Biology (JCB), 22(9): 844-860, 2015.

J27: Rudy Clauseng, Buyong Ma, Ruth Nussinov, and Amarda Shehu*. Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm. PLoS Computational Biology (PCB) 11(9): e1004470, 2015.

J26: Uday Kamathg, Kenneth A De Jong*, and Amarda Shehu*. Effective Automated Feature Construction and Selection for Classification of Biological Sequences. PLoS One, 9(7): e99982, 2014.

J25: Kevin Molloyg, M. Jennifer Vanu, Daniel Barbara*, and Amarda Shehu*. Exploring Representations of Protein Structure for Automated Remote Homology Detection and Mapping of Protein Structure Space. BMC Bioinformatics 15 (Suppl 8):S4, 2014.

J24: Nadine Kabbani*, Jacob C. Nordman, Brian Corgiat, Daniel Veltrig, Amarda Shehu, and David J. Adams. Are Nicotinic Receptors Coupled to G Proteins? BioEssays 35(12): 1025–1034, 2013, (selected for journal front cover video display. Read the highlight written on our article in same issue by Edward Howrot.)

J23: Abrar Ashoor, Jacob C. Nordman, Daniel Veltrig, Keun-Hang Susan Yang, Lina Al Kury, Yaroslav Shuba, Mohamed Mahgoub, Frank C. Howarth, Carl Lupica, Amarda Shehu, Nadine Kabbani, and Murat Oz*. Menthol Inhibits 5-HT3 Receptor-mediated Currents. J of Pharmacology and Experimental Therapeutics (JPET) 347(2):398-409, 2013, (selected for issue front cover).

J22: Abrar Ashoor, Jacob C. Nordman, Daniel Veltrig, Keun-Hang Susan Yang, Lina Al Kury, Yaroslav Shuba, Mohamed Mahgoub, Frank C. Howarth, Bassem Sadek, Amarda Shehu, Nadine Kabbani, and Murat Oz*. Menthol Binding and Inhibition of Alpha7-nicotinic Acetylcholine Receptors. PLos One 8(7):e67674, 2013.

J21: Kevin Molloyg, Sameh Salehu, and Amarda Shehu*. Probabilistic Search and Energy Guidance for Biased Decoy Sampling in Ab-initio Protein Structure Prediction. IEEE/ACM Trans Comp Biol and Bioinf 10(5):1162-1175, 2013.

J20: Irina Hashmig and Amarda Shehu*. HopDock: A Probabilistic Search Algorithm for Decoy Sampling in Protein-protein Docking. Proteome Sci 11(Suppl1):S6, 2013.

J19: Sameh Salehu, Brian Olsong, and Amarda Shehu*. A population-based evolutionary search approach to the multiple minima problem in de novo protein structure prediction. BMC Structural Biology J 13(Suppl1):S4, 2013.

J18: Brian Olsong and Amarda Shehu*. Rapid Sampling of Local Minima in Protein Energy Surface and Effective Reduction through a Multi-objective Filter. Proteome Sci 11(Suppl1):S12, 2013.

J17: Kevin Molloyg and Amarda Shehu*. Elucidating the Ensemble of Functionally-relevant Transitions in Protein Systems with a Robotics-inspired Method. BMC Structural Biology J: 13(Suppl1):S8, 2013.

J16: Brian Olsong, Irina Hashmig, Kevin Molloyg, and Amarda Shehu*. Basin Hopping as a General and Versatile Optimization Framework for the Characterization of Biological Macromolecules. Advances in Artificial Intelligence J: 2012, 674832 (special issue on Artificial Intelligence Applications in Biomedicine).

J15: Brian Olsong and Amarda Shehu*. Evolutionary-inspired Probabilistic Search for Enhancing Sampling of Local Minima in the Protein Energy Surface. Proteome Science: 2012, 10(Suppl1): S5.

J14: Irina Hashmig, Bahar Aklbal-Delibas, Nurit Haspel, and Amarda Shehu*. Guiding Protein Docking with Geometric and Evolutionary Information. J Bioinf and Comp Biol: 2012, 10(3): 1242002.

J13: Bahar Aklbal-Delibas, Irina Hashmig, Amarda Shehu, and Nurit Haspel*. An Evolutionary Conservation Based Method for Re fining and Reranking Protein Complex Structures. J Bioinf and Comp Biol: 2012, 10(3):1242008.

J12: Brian Olsong, Kevin Molloyg, S.-Farid Hendig, and Amarda Shehu*. Guiding Search in the Protein Conformational Space with Structural Profiles. J Bioinf and Comp Biol: 2012, 10(3):1242005.

J11: Amarda Shehu* and Lydia Kavraki*. Modeling Structures and Motions of Loops in Protein Molecules. Entropy: 2012, 14(2):252-290 (invited review article), IF 2011: 1.109).

J10: Uday Kamathg, Jack Comptonu, Rezarta Islamaj Dogan, Kenneth A. De Jong*, and Amarda Shehu*. An Evolutionary Algorithm Approach for Feature Generation from Sequence Data and its Application to DNA Splice-Site Prediction. IEEE Trans Comp Biol and Bioinf: 2012, 9(5):1387-1398 (IF 2011: 2.25).

J9: Uday Kamathg, Amarda Shehu*, and Kenneth A. De Jong*. A Two-Stage Evolutionary Approach for Effective Classification of Hypersensitive DNA Sequences. J Bioinf and Comp Biol: 2011, 9(3): 399-413.

J8: Brian Olsong, Kevin Molloyg, and Amarda Shehu*. In Search of the Protein Native State with a Probabilistic Sampling Approach. J Bioinf and Comp Biol: 2011, 9(3):383-398.

Book chapters

B4: Amarda Shehu, Daniel Barbara, and K. Molloy. A Survey of Computational Methods for Protein Function Prediction. In Big Data Analytics in Genomics (Springer), first edition, (Editors: Wong, K. C.), 2016.

B3: Amarda Shehu. A Review of Evolutionary Algorithms for Computing Functional Conformations of Protein Molecules. In Computer-Aided Drug Discovery (Springer Methods in Pharmacology and Toxicology Series), first edition, (Editors: Wei Zhang), 2015.

B2: Amarda Shehu. Probabilistic Search and Optimization for Protein Energy Landscapes. In Handbook of Computational Molecular Biology (Chapman & Hall/CRC Computer & Information Science Series), second edition, (Editors: Srinivas Aluru and Mona Singh), 2013.

B1: Amarda Shehu. Conformational Search for the Protein Native State. In Introduction to Protein Structure Prediction: Methods and Algorithms (eds H. Rangwala and G. Karypis), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 0.1002/9780470882207.ch19, September, 2010.


Created in 2017.  Last update: January, 2019.


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