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ORCIDAmarda Shehu
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- affiliation: George Mason University, Fairfax VA, USA
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2020 – today
- 2024
[c100]Sam Blouir, Jimmy T. H. Smith, Antonios Anastasopoulos, Amarda Shehu:
Birdie: Advancing State Space Language Modeling with Dynamic Mixtures of Training Objectives. EMNLP 2024: 9679-9705- [c99]Toki Tahmid Inan
, Amarda Shehu:
Revisiting Evolutionary Algorithms for Optimization for Deep Learning: Introducing DL-HEA: EAs for Optimization for Deep Learning. GECCO Companion 2024: 435-438 - [i13]Toki Tahmid Inan, Mingrui Liu, Amarda Shehu:
Beyond Single-Model Views for Deep Learning: Optimization versus Generalizability of Stochastic Optimization Algorithms. CoRR abs/2403.00574 (2024) - [i12]Yuanjie Lu, Amarda Shehu, David Lattanzi:
Accounting for Work Zone Disruptions in Traffic Flow Forecasting. CoRR abs/2407.11407 (2024) - [i11]Sam Blouir, Jimmy T. H. Smith, Antonios Anastasopoulos, Amarda Shehu:
Birdie: Advancing State Space Models with Reward-Driven Objectives and Curricula. CoRR abs/2411.01030 (2024) - 2023
- [j44]Anowarul Kabir, Manish Bhattarai, Kim Ø. Rasmussen, Amarda Shehu, Anny Usheva, Alan R. Bishop, Boian S. Alexandrov:
Examining DNA breathing with pyDNA-EPBD. Bioinform. 39(10) (2023) - [j43]Ahmed Bin Zaman, Toki Tahmid Inan, Kenneth A. De Jong, Amarda Shehu:
Adaptive Stochastic Optimization to Improve Protein Conformation Sampling. IEEE ACM Trans. Comput. Biol. Bioinform. 20(5): 2759-2771 (2023) - [c98]Anowarul Kabir, Asher Moldwin, Amarda Shehu:
A Comparative Analysis of Transformer-based Protein Language Models for Remote Homology Prediction. BCB 2023: 97:1-97:9 - [c97]Megan Herceg, Amarda Shehu:
Structure- and Energy-based Analysis of Small Molecule Ligand Binding to Steroid Nuclear Receptors. BCB 2023: 105:1-105:9 - [c96]Yajie Bao, Amarda Shehu, Mingrui Liu:
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization. NeurIPS 2023 - 2022
- [j42]Yuanqi Du, Xiaojie Guo, Yinkai Wang, Amarda Shehu, Liang Zhao:
Small molecule generation via disentangled representation learning. Bioinform. 38(12): 3200-3208 (2022) - [j41]Parastoo Kamranfar, David Lattanzi, Amarda Shehu, Shelley Stoffels:
Pavement Distress Recognition via Wavelet-Based Clustering of Smartphone Accelerometer Data. J. Comput. Civ. Eng. 36(4) (2022) - [j40]Nasrin Akhter, Kazi Lutful Kabir, Gopinath Chennupati, Raviteja Vangara, Boian S. Alexandrov, Hristo N. Djidjev, Amarda Shehu:
Improved Protein Decoy Selection via Non-Negative Matrix Factorization. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1670-1682 (2022) - [c95]Bo Pan, Yinkai Wang, Xuanyang Lin, Muran Qin, Yuanqi Du, Shiva Ghaemi, Aowei Ding, Shiyu Wang, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Ashley Ann Petersen, Austin Leitgeb, Amarda Shehu, Liang Zhao:
Property-Controllable Generation of Quaternary Ammonium Compounds. BIBM 2022: 3462-3469 - [c94]Taseef Rahman, Fardina Fathmiul Alam, Amarda Shehu:
Equivariant Encoding based GVAE (EqEn-GVAE) for Protein Tertiary Structure Generation. BIBM 2022: 3470-3477 - [c93]Yinkai Wang, Shiva Ghaemi, Aowei Ding, Yuanqui Du, Bo Pan, Muran Qin, Xuanyang Lin, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Liang Zhao, Amarda Shehu:
Generation and Characterization of Quaternary Ammonium Compounds via Deep Learning. BIBM 2022: 3512-3519 - [c92]Toki Tahmid Inan, Mingrui Liu, Amarda Shehu:
F-Measure Optimization for Multi-class, Imbalanced Emotion Classification Tasks. ICANN (1) 2022: 158-170 - [c91]Anowarul Kabir, Amarda Shehu:
Sequence-Structure Embeddings via Protein Language Models Improve on Prediction Tasks. ICKG 2022: 105-112 - [c90]Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Amarda Shehu, Liang Zhao:
Multi-objective Deep Data Generation with Correlated Property Control. NeurIPS 2022 - [c89]Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao:
Interpretable Molecular Graph Generation via Monotonic Constraints. SDM 2022: 73-81 - [i10]Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao:
Interpretable Molecular Graph Generation via Monotonic Constraints. CoRR abs/2203.00412 (2022) - [i9]Anowarul Kabir, Amarda Shehu:
Transformer Neural Networks Attending to Both Sequence and Structure for Protein Prediction Tasks. CoRR abs/2206.11057 (2022) - [i8]Parastoo Kamranfar, David Lattanzi, Amarda Shehu, Daniel Barbará:
Multiple Instance Learning for Detecting Anomalies over Sequential Real-World Datasets. CoRR abs/2210.01707 (2022) - [i7]Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Amarda Shehu, Liang Zhao:
Multi-objective Deep Data Generation with Correlated Property Control. CoRR abs/2210.01796 (2022) - 2021
- [j39]Fardina Fathmiul Alam, Amarda Shehu:
Unsupervised multi-instance learning for protein structure determination. J. Bioinform. Comput. Biol. 19(1): 2140002:1-2140002:20 (2021) - [c88]Yuanqi Du, Yinkai Wang, Fardina Fathmiul Alam, Yuanjie Lu, Xiaojie Guo, Liang Zhao, Amarda Shehu:
Deep Latent-Variable Models for Controllable Molecule Generation. BIBM 2021: 372-375 - [c87]Vedant Vajre, Mitchell Naylor, Uday Kamath, Amarda Shehu:
PsychBERT: A Mental Health Language Model for Social Media Mental Health Behavioral Analysis. BIBM 2021: 1077-1082 - [c86]Fardina Fathmiul Alam, Amarda Shehu:
Generating Physically-Realistic Tertiary Protein Structures with Deep Latent Variable Models Learning Over Experimentally-available Structures. BIBM 2021: 2463-2470 - [c85]Kazi Lutful Kabir, Ruth Nussinov, Buyong Ma, Amarda Shehu:
Antigen Binding Reshapes Antibody Energy Landscape and Conformation Dynamics. BIBM 2021: 2519-2526 - [c84]Zahra Rajabi, Özlem Uzuner, Amarda Shehu:
Detecting Scarce Emotions Using BERT and Hyperparameter Optimization. ICANN (5) 2021: 383-395 - [c83]Kazi Lutful Kabir, Manish Bhattarai, Boian S. Alexandrov, Amarda Shehu:
Single Model Quality Estimation of Protein Structures via Non-negative Tensor Factorization. ICCABS 2021: 3-15 - [c82]Taseef Rahman, Yuanqi Du, Amarda Shehu:
Graph Representation Learning for Protein Conformation Sampling. ICCABS 2021: 16-28 - [d5]Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao:
Dataset for Disentangled Representation Learning for Interpretable Molecule Generation. IEEE DataPort, 2021
- [d4]Wanli Qiao, Amarda Shehu:
Dataset for Space Partitioning and Regression Mode Seeking via a Mean-Shift-Inspired Algorithm. IEEE DataPort, 2021 - [d3]Taseef Rahman, Yuanqi Du, Liang Zhao, Amarda Shehu:
Dataset for Generative Adversarial Learning of Protein Tertiary Structures. Molecules, 2021. IEEE DataPort, 2021 - [d2]Ahmed Bin Zaman, Toki Tahmid Inan, Kenneth A. De Jong, Amarda Shehu:
Adaptive Conformation Sampling Dataset Zaman_TCBB21. IEEE DataPort, 2021 - [i6]Wanli Qiao, Amarda Shehu:
Space Partitioning and Regression Mode Seeking via a Mean-Shift-Inspired Algorithm. CoRR abs/2104.10103 (2021) - [i5]Yuanjie Lu, Parastoo Kamranfar, David Lattanzi, Amarda Shehu:
Traffic Flow Forecasting with Maintenance Downtime via Multi-Channel Attention-Based Spatio-Temporal Graph Convolutional Networks. CoRR abs/2110.01535 (2021) - 2020
- [j38]Nasrin Akhter, Gopinath Chennupati, Hristo N. Djidjev, Amarda Shehu:
Decoy selection for protein structure prediction via extreme gradient boosting and ranking. BMC Bioinform. 21-S(1): 189 (2020) - [c81]Fardina Fathmiul Alam, Amarda Shehu:
Variational Autoencoders for Protein Structure Prediction. BCB 2020: 27:1-27:10 - [c80]Xiao Chen, Nasrin Akhter, Zhiye Guo, Tianqi Wu, Jie Hou, Amarda Shehu, Jianlin Cheng:
Deep Ranking in Template-free Protein Structure Prediction. BCB 2020: 31:1-31:10 - [c79]Kazi Lutful Kabir, Gopinath Chennupati, Raviteja Vangara, Hristo N. Djidjev, Boian S. Alexandrov, Amarda Shehu:
Decoy Selection in Protein Structure Determination via Symmetric Non-negative Matrix Factorization. BIBM 2020: 23-28 - [c78]Ahmed Bin Zaman, Toki Tahmid Inan, Amarda Shehu:
Protein Decoy Generation via Adaptive Stochastic Optimization for Protein Structure Determination. BIBM 2020: 50-55 - [c77]Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye:
Interpretable Deep Graph Generation with Node-edge Co-disentanglement. KDD 2020: 1697-1707 - [c76]Jing Lei, Nasrin Akhter, Wanli Qiao, Amarda Shehu:
Reconstruction and Decomposition of High-Dimensional Landscapes via Unsupervised Learning. KDD 2020: 2505-2513 - [c75]Zahra Rajabi, Amarda Shehu, Özlem Uzuner:
A Multi-channel BiLSTM-CNN Model for Multilabel Emotion Classification of Informal Text. ICSC 2020: 303-306 - [d1]Ahmed Bin Zaman, Parastoo Kamranfar, Carlotta Domeniconi, Amarda Shehu:
Protein Tertiary Structures Zaman_Molecules20. IEEE DataPort, 2020 - [i4]Xiaojie Guo, Sivani Tadepalli, Liang Zhao, Amarda Shehu:
Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder. CoRR abs/2004.07119 (2020) - [i3]Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye:
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement. CoRR abs/2006.05385 (2020) - [i2]Nasrin Akhter, Gopinath Chennupati, Hristo N. Djidjev, Amarda Shehu:
Decoy Selection for Protein Structure Prediction Via Extreme Gradient Boosting and Ranking. CoRR abs/2010.01441 (2020)
2010 – 2019
- 2019
- [j37]Ahmed Bin Zaman, Amarda Shehu:
Balancing multiple objectives in conformation sampling to control decoy diversity in template-free protein structure prediction. BMC Bioinform. 20(1): 211:1-211:17 (2019) - [j36]David Morris, Tatiana Maximova, Erion Plaku, Amarda Shehu:
Attenuating dependence on structural data in computing protein energy landscapes. BMC Bioinform. 20-S(11): 280:1-280:10 (2019) - [j35]Ahmed Bin Zaman, Amarda Shehu:
Building maps of protein structure spaces in template-free protein structure prediction. J. Bioinform. Comput. Biol. 17(6): 1940013:1-1940013:17 (2019) - [j34]Kazi Lutful Kabir, Nasrin Akhter, Amarda Shehu:
From molecular energy landscapes to equilibrium dynamics via landscape analysis and markov state models. J. Bioinform. Comput. Biol. 17(6): 1940014:1-1940014:21 (2019) - [j33]Amarda Shehu, Giuseppe Pozzi, Tamer Kahveci:
Guest Editorial for the ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. IEEE ACM Trans. Comput. Biol. Bioinform. 16(5): 1409 (2019) - [j32]Tamer Kahveci, Giuseppe Pozzi, Amarda Shehu, May Dongmei Wang:
Guest Editorial on the Special Issue on Informatics on Biomedical Data Learning, Reasoning, and Representation. IEEE J. Biomed. Health Informatics 23(1): 81-82 (2019) - [c74]Ahmed Bin Zaman, Prasanna Venkatesh Parthasarathy, Amarda Shehu:
Using Sequence-Predicted Contacts to Guide Template-free Protein Structure Prediction. BCB 2019: 154-160 - [c73]Ahmed Bin Zaman, Parastoo Kamranfar, Carlotta Domeniconi, Amarda Shehu:
Decoy Ensemble Reduction in Template-free Protein Structure Prediction. BCB 2019: 562-567 - [c72]Fardina Fathmiul Alam, Taseef Rahman, Amarda Shehu:
Learning Reduced Latent Representations of Protein Structure Data. BCB 2019: 592-597 - [c71]Sivani Tadepalli, Nasrin Akhter, Daniel Barbará, Amarda Shehu:
Identifying Near-Native Protein Structures via Anomaly Detection. BIBM 2019: 30-35 - [c70]Nasrin Akhter, Raviteja Vangara, Gopinath Chennupati, Boian S. Alexandrov, Hristo N. Djidjev, Amarda Shehu:
Non-Negative Matrix Factorization for Selection of Near-Native Protein Tertiary Structures. BIBM 2019: 70-73 - [c69]Ahmed Bin Zaman, Kenneth A. De Jong, Amarda Shehu:
Using subpopulation EAs to map molecular structure landscapes. GECCO 2019: 960-967 - [c68]Zahra Rajabi, Amarda Shehu, Hemant Purohit:
User Behavior Modelling for Fake Information Mitigation on Social Web. SBP-BRiMS 2019: 234-244 - [p1]Uday Kamath, Carlotta Domeniconi, Amarda Shehu, Kenneth A. De Jong:
EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications. Innovations in Big Data Mining and Embedded Knowledge 2019: 35-59 - [i1]Kevin Molloy, Erion Plaku, Amarda Shehu:
ROMEO: A Plug-and-play Software Platform of Robotics-inspired Algorithms for Modeling Biomolecular Structures and Motions. CoRR abs/1905.08331 (2019) - 2018
- [j31]Daniel Veltri, Uday Kamath, Amarda Shehu:
Deep learning improves antimicrobial peptide recognition. Bioinform. 34(16): 2740-2747 (2018) - [j30]Nasrin Akhter, Wanli Qiao, Amarda Shehu:
An Energy Landscape Treatment of Decoy Selection in Template-Free Protein Structure Prediction. Comput. 6(2): 39 (2018) - [j29]Tatiana Maximova, Zijing Zhang, Daniel Carr, Erion Plaku, Amarda Shehu:
Sample-Based Models of Protein Energy Landscapes and Slow Structural Rearrangements. J. Comput. Biol. 25(1): 33-50 (2018) - [j28]Julia Handl, Amarda Shehu, José Santos Reyes:
Advances in the Application and Development of Non-Linear Global Optimization Techniques in Computational Structural Biology. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 688-689 (2018) - [j27]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
From Optimization to Mapping: An Evolutionary Algorithm for Protein Energy Landscapes. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 719-731 (2018) - [j26]Tatiana Maximova, Erion Plaku, Amarda Shehu:
Structure-Guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm. IEEE ACM Trans. Comput. Biol. Bioinform. 15(6): 1783-1796 (2018) - [c67]Sharmila Roychoudhury, Amarda Shehu:
Analysis of Molecular Structure Data]{Systematic Study of Different Design Decisions in Markov Model-based Analysis of Molecular Structure Data: Extended Abstract. BCB 2018: 508-509 - [c66]Kevin Molloy, Nasrin Akhter, Amarda Shehu:
Modeling Macromolecular Structures and Motions: Computational Methods for Sampling and Analysis of Energy Landscapes. BCB 2018: 554 - [c65]Fahad Almsned, Gideon Gogovi, Nicole Bracci, Kylene Kehn-Hall, Estela Blaisten-Barojas, Amarda Shehu:
Modeling the Tertiary Structure of a Multi-domain Protein: Structure Prediction of Multi-domain Proteins. BCB 2018: 615-620 - [c64]Liban Hassan, Zahra Rajabi, Nasrin Akhter, Amarda Shehu:
Community Detection for Decoy Selection in Template-free Protein Structure Prediction. BCB 2018: 621-627 - [c63]Nasrin Akhter, Jing Lei, Wanli Qiao, Amarda Shehu:
Reconstructing and Decomposing Protein Energy Landscapes to Organize Structure Spaces and Reveal Biologically-active States. BIBM 2018: 56-60 - [c62]Manpriya Dua, Daniel Veltri, Barney Bishop, Amarda Shehu:
Guiding Exploration of Antimicrobial Peptide Space with a Deep Neural Network. BIBM 2018: 2082-2087 - [c61]Nasrin Akhter, Gopinath Chennupati, Hristo N. Djidjev, Amarda Shehu:
Improved Decoy Selection via Machine Learning and Ranking. ICCABS 2018: 1 - [e3]Amarda Shehu, Cathy H. Wu, Christina Boucher, Jing Li, Hongfang Liu, Mihai Pop:
Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB 2018, Washington, DC, USA, August 29 - September 01, 2018. ACM 2018 [contents] - 2017
- [j25]Illhoi Yoo, Amarda Shehu:
Guest Editorial for Special Section on BIBM 2014. IEEE ACM Trans. Comput. Biol. Bioinform. 14(2): 252-253 (2017) - [j24]Daniel Veltri, Uday Kamath, Amarda Shehu:
Improving Recognition of Antimicrobial Peptides and Target Selectivity through Machine Learning and Genetic Programming. IEEE ACM Trans. Comput. Biol. Bioinform. 14(2): 300-313 (2017) - [c60]Kevin Molloy, David Morris, Amarda Shehu:
ACM-BCB '17 Tutorial: Robotics-inspired Algorithms for Modeling Protein Structures and Motions. BCB 2017: 628 - [c59]Amarda Shehu, Tamer Kahveci, Giuseppe Pozzi:
Highlights Talks at ACM BCB 2017. BCB 2017: 635 - [c58]Nurit Haspel, Amarda Shehu, Kevin Molloy:
The 2017 Computational Structural Bioinformatics Workshop: CSBW 2017. BCB 2017: 643 - [c57]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolving Conformation Paths to Model Protein Structural Transitions. BCB 2017: 673-678 - [c56]Wanli Qiao, Tatiana Maximova, Erion Plaku, Amarda Shehu:
Statistical Analysis of Computed Energy Landscapes to Understand Dysfunction in Pathogenic Protein Variants. BCB 2017: 679-684 - [c55]Wanli Qiao, Tatiana Maximova, Xiaowen Fang, Erion Plaku, Amarda Shehu:
Reconstructing and mining protein energy landscape to understand disease. BIBM 2017: 22-27 - [c54]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Modeling protein structural transitions as a multiobjective optimization problem. CIBCB 2017: 1-8 - [c53]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolutionary search for paths on protein energy landscapes. GECCO (Companion) 2017: 77-78 - [c52]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
An evolutionary algorithm to model structural excursions of a protein. GECCO (Companion) 2017: 1669-1673 - [c51]David Morris, Tatiana Maximova, Erion Plaku, Amarda Shehu:
Out of one, many: Exploiting intrinsic motions to explore protein structure spaces. ICCABS 2017: 1 - [e2]Nurit Haspel, Lenore J. Cowen, Amarda Shehu, Tamer Kahveci, Giuseppe Pozzi:
Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB 2017, Boston, MA, USA, August 20-23, 2017. ACM 2017, ISBN 978-1-4503-4722-8 [contents] - 2016
- [j23]Amarda Shehu, Erion Plaku:
A Survey of Computational Treatments of Biomolecules by Robotics-Inspired Methods Modeling Equilibrium Structure and Dynamic. J. Artif. Intell. Res. 57: 509-572 (2016) - [j22]Tatiana Maximova, Ryan Moffatt, Buyong Ma, Ruth Nussinov, Amarda Shehu:
Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics. PLoS Comput. Biol. 12(4) (2016) - [j21]Lydia Tapia, Juan Cortés, Amarda Shehu, Jinalin Chen:
Foreword on special issue on robotics methods for structural and dynamic modeling of molecular systems. Robotica 34(8): 1677-1678 (2016) - [j20]Kevin Molloy, Rudy Clausen, Amarda Shehu:
A stochastic roadmap method to model protein structural transitions. Robotica 34(8): 1705-1733 (2016) - [c50]Tatiana Maximova, Daniel Carr, Erion Plaku, Amarda Shehu:
Sample-based Models of Protein Structural Transitions. BCB 2016: 128-137 - [c49]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
A Novel EA-based Memetic Approach for Efficiently Mapping Complex Fitness Landscapes. GECCO 2016: 85-92 - [c48]José Santos Reyes, Julia Handl, Amarda Shehu:
Workshop Evolutionary Computation in Computational Structural Biology 2016 Chairs' Welcome. GECCO (Companion) 2016: 1283-1284 - [c47]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Path-based Guidance of an Evolutionary Algorithm in Mapping a Fitness Landscape and its Connectivity. GECCO (Companion) 2016: 1293-1298 - [c46]Carola Doerr, Julia Handl, Emma Hart, Gabriela Ochoa, Amarda Shehu, Tea Tusar, Anya E. Vostinar, Christine Zarges, Nur Zincir-Heywood:
Women@GECCO 2016 Chairs' Welcome. GECCO (Companion) 2016: 1447-1449 - 2015
- [j19]Jing He, Amarda Shehu, Nurit Haspel, Brian Chen:
The 7th Computational Structural Bioinformatics Workshop. J. Comput. Biol. 22(9): 785-786 (2015) - [j18]Irina Hashmi, Amarda Shehu:
idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking. J. Comput. Biol. 22(9): 806-822 (2015) - [j17]Rudy Clausen, Amarda Shehu:
A Data-Driven Evolutionary Algorithm for Mapping Multibasin Protein Energy Landscapes. J. Comput. Biol. 22(9): 844-860 (2015) - [j16]Rudy Clausen, Buyong Ma, Ruth Nussinov, Amarda Shehu:
Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm. PLoS Comput. Biol. 11(9) (2015) - [j15]Amarda Shehu, Ruth Nussinov:
Computational Methods for Exploration and Analysis of Macromolecular Structure and Dynamics. PLoS Comput. Biol. 11(10) (2015) - [c45]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolutionary search strategies for efficient sample-based representations of multiple-basin protein energy landscapes. BIBM 2015: 13-20 - [c44]Tatiana Maximova, Erion Plaku, Amarda Shehu:
Computing transition paths in multiple-basin proteins with a probabilistic roadmap algorithm guided by structure data. BIBM 2015: 35-42 - [c43]Rudy Clausen, Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolution Strategies for Exploring Protein Energy Landscapes. GECCO 2015: 217-224 - [c42]Amarda Shehu, Kenneth A. De Jong:
Evolutionary Algorithms for Protein Structure Modeling. GECCO (Companion) 2015: 533-545 - [c41]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Mapping Multiple Minima in Protein Energy Landscapes with Evolutionary Algorithms. GECCO (Companion) 2015: 923-927 - [c40]Kevin Molloy, Amarda Shehu:
Interleaving Global and Local Search for Protein Motion Computation. ISBRA 2015: 175-186 - [e1]Jun Huan, Satoru Miyano, Amarda Shehu, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Vijay K. Gombar, Matthieu-P. Schapranow, Illhoi Yoo, Jiayu Zhou, Brian Chen, Vinay Pai, Brian G. Pierce:
2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, Washington, DC, USA, November 9-12, 2015. IEEE Computer Society 2015, ISBN 978-1-4673-6799-8 [contents] - 2014
- [j14]Kevin Molloy, M. Jennifer Van, Daniel Barbará, Amarda Shehu:
Exploring representations of protein structure for automated remote homology detection and mapping of protein structure space. BMC Bioinform. 15(S-8): S4 (2014) - [c39]Rudy Clausen, Amarda Shehu:
A multiscale hybrid evolutionary algorithm to obtain sample-based representations of multi-basin protein energy landscapes. BCB 2014: 269-278 - [c38]Irina Hashmi, Daniel Veltri, Nadine Kabbani, Amarda Shehu:
Knowledge-based search and multi-objective filters: proposed structural models of GPCR dimerization. BCB 2014: 279-288 - [c37]Didier Devaurs, Amarda Shehu, Thierry Siméon, Juan Cortés:
Sampling-based methods for a full characterization of energy landscapes of small peptides. BIBM 2014: 37-44 - [c36]Daniel Veltri, Uday Kamath, Amarda Shehu:
A novel method to improve recognition of antimicrobial peptides through distal sequence-based features. BIBM 2014: 371-378 - [c35]Amarda Shehu, Kenneth A. De Jong:
Evolutionary search algorithms for protein modeling: from de novo structure prediction to comprehensive maps of functionally-relevant structures of protein chains and assemblies. GECCO (Companion) 2014: 839-856 - 2013
- [j13]Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher W. Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Dimitri Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O'Sullivan, Marc Pickett, Vedran Podobnik, David Poole, Lokendra Shastri, Amarda Shehu, Gita Sukthankar:
The AAAI-13 Conference Workshops. AI Mag. 34(4): 9- (2013) - [j12]Kevin Molloy, Sameh N. Saleh, Amarda Shehu:
Probabilistic Search and Energy Guidance for Biased Decoy Sampling in Ab Initio Protein Structure Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 10(5): 1162-1175 (2013) - [c34]Elena G. Randou, Daniel Veltri, Amarda Shehu:
Binary Response Models for Recognition of Antimicrobial Peptides. BCB 2013: 76 - [c33]Brian S. Olson, Amarda Shehu:
Multi-Objective Stochastic Search for Sampling Local Minima in the Protein Energy Surface. BCB 2013: 430 - [c32]Irina Hashmi, Amarda Shehu:
Protein-protein Docking Using Information from Native Interaction Interfaces. BCB 2013: 670 - [c31]Rudy Clausen, Amarda Shehu:
A PCA-guided Search Algorithm to Probe the Conformational Space of the Ras Protein. BCB 2013: 679 - [c30]Rudy Clausen, Amarda Shehu:
Exploring the Structure Space of Wildtype Ras Guided by Experimental Data. BCB 2013: 756 - [c29]Irina Hashmi, Amarda Shehu:
Informatics-driven Protein-protein Docking. BCB 2013: 771 - [c28]Brian S. Olson, Kenneth A. De Jong, Amarda Shehu:
Off-lattice protein structure prediction with homologous crossover. GECCO 2013: 287-294 - [c27]Kevin Molloy, M. Jennifer Van, Daniel Barbará, Amarda Shehu:
Higher-order representations of protein structure space. ICCABS 2013: 1-2 - [c26]Elena G. Randou, Daniel Veltri, Amarda Shehu:
Systematic analysis of global features and model building for recognition of antimicrobial peptides. ICCABS 2013: 1-6 - 2012
- [j11]Brian S. Olson, Irina Hashmi, Kevin Molloy, Amarda Shehu:
Basin Hopping as a General and Versatile Optimization Framework for the Characterization of Biological Macromolecules. Adv. Artif. Intell. 2012: 674832:1-674832:19 (2012) - [j10]Amarda Shehu, Lydia E. Kavraki:
Modeling Structures and Motions of Loops in Protein Molecules. Entropy 14(2): 252-290 (2012) - [j9]Bahar Akbal-Delibas, Irina Hashmi, Amarda Shehu, Nurit Haspel:
An Evolutionary conservation-Based Method for Refining and Reranking protein Complex Structures. J. Bioinform. Comput. Biol. 10(3) (2012) - [j8]Irina Hashmi, Bahar Akbal-Delibas, Nurit Haspel, Amarda Shehu:
Guiding protein docking with Geometric and Evolutionary Information. J. Bioinform. Comput. Biol. 10(3) (2012) - [j7]Brian S. Olson, Kevin Molloy, S. Farid Hendi, Amarda Shehu:
Guiding Probabilistic Search of the protein conformational Space with Structural Profiles. J. Bioinform. Comput. Biol. 10(3) (2012) - [j6]Uday Kamath, Jack Compton, Rezarta Islamaj Dogan, Kenneth A. De Jong, Amarda Shehu:
An Evolutionary Algorithm Approach for Feature Generation from Sequence Data and Its Application to DNA Splice Site Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 9(5): 1387-1398 (2012) - [c25]Kevin Molloy, Amarda Shehu:
Biased decoy sampling to aid the selection of near-native protein conformations. BCB 2012: 131-138 - [c24]Brian S. Olson, Amarda Shehu:
An evolutionary search framework to efficiently sample local minima in the protein conformational space. BCB 2012: 590 - [c23]Irina Hashmi, Amarda Shehu:
A basin hopping algorithm for protein-protein docking. BIBM 2012: 1-4 - [c22]Brian S. Olson, Amarda Shehu:
Efficient basin hopping in the protein energy surface. BIBM 2012: 1-6 - [c21]Kevin Molloy, Amarda Shehu:
A robotics-inspired method to sample conformational paths connecting known functionally-relevant structures in protein systems. BIBM Workshops 2012: 56-63 - [c20]Sameh N. Saleh, Brian S. Olson, Amarda Shehu:
A population-based evolutionary algorithm for sampling minima in the protein energy surface. BIBM Workshops 2012: 64-71 - [c19]Sameh N. Saleh, Brian S. Olson, Amarda Shehu:
An evolutionary framework to sample near-native protein conformations. BIBM Workshops 2012: 933 - [c18]Daniel Veltri, Amarda Shehu:
Physico-chemical features for recognition of antimicrobial peptides. BIBM Workshops 2012: 942 - [c17]Brian S. Olson, Amarda Shehu:
Jumping low, jumping high: Controlling hopping in the protein energy surface. BIBM Workshops 2012: 946 - [c16]Irina Hashmi, Amarda Shehu:
Sampling low-energy protein-protein configurations with basin hopping. BIBM Workshops 2012: 947 - [c15]Kevin Molloy, Amarda Shehu:
Mapping conformational pathways between known functional protein states. BIBM Workshops 2012: 971 - [c14]Kevin Molloy, Amarda Shehu:
A tree-based search to bias sampling of protein decoy conformations. BIBM Workshops 2012: 978 - [c13]Uday Kamath, Johan Kaers, Amarda Shehu, Kenneth A. De Jong:
A Spatial EA Framework for Parallelizing Machine Learning Methods. PPSN (1) 2012: 206-215 - 2011
- [j5]Nurit Haspel, Amarda Shehu:
The 5th International Conference on Bio-Inspired Models of Network, Information and Computing Systems (Bionetics 2010) Special Track on Bioinformatics. J. Bioinform. Comput. Biol. 9(3) (2011) - [j4]Brian S. Olson, Kevin Molloy, Amarda Shehu:
In Search of the protein Native State with a Probabilistic Sampling Approach. J. Bioinform. Comput. Biol. 9(3): 383-398 (2011) - [j3]Uday Kamath, Amarda Shehu, Kenneth A. De Jong:
A Two-Stage Evolutionary Approach for Effective Classification of hypersensitive DNA Sequences. J. Bioinform. Comput. Biol. 9(3): 399-413 (2011) - [c12]Brian S. Olson, Amarda Shehu:
Populating Local Minima in the Protein Conformational Space. BIBM 2011: 114-117 - [c11]Irina Hashmi, Bahar Akbal-Delibas, Nurit Haspel, Amarda Shehu:
Protein docking with information on evolutionary conserved interfaces. BIBM Workshops 2011: 358-365 - [c10]Brian S. Olson, S. Farid Hendi, Amarda Shehu:
Protein conformational search with geometric projections. BIBM Workshops 2011: 366-373 - [c9]Bahar Akbal-Delibas, Irina Hashmi, Amarda Shehu, Nurit Haspel:
Refinement of docked protein complex structures using evolutionary traces. BIBM Workshops 2011: 400-404 - [c8]Kevin Molloy, Amarda Shehu:
Assembly of low-energy protein conformations with heterogeneous fragments. BIBM Workshops 2011: 991-993 - [c7]Uday Kamath, Kenneth A. De Jong, Amarda Shehu:
An evolutionary-based approach for feature generation: Eukaryotic promoter recognition. IEEE Congress on Evolutionary Computation 2011: 277-284 - 2010
- [j2]Amarda Shehu, Brian S. Olson:
Guiding the Search for Native-like Protein Conformations with an Ab-initio Tree-based Exploration. Int. J. Robotics Res. 29(8): 1106-1127 (2010) - [c6]Uday Kamath, Amarda Shehu, Kenneth A. De Jong:
Feature and Kernel Evolution for Recognition of Hypersensitive Sites in DNA Sequences. BIONETICS 2010: 213-228 - [c5]Brian S. Olson, Kevin Molloy, Amarda Shehu:
Enhancing Sampling of the Conformational Space Near the Protein Native State. BIONETICS 2010: 249-263 - [c4]Uday Kamath, Amarda Shehu, Kenneth A. De Jong:
Using evolutionary computation to improve SVM classification. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c3]Uday Kamath, Kenneth A. De Jong, Amarda Shehu:
Selecting predictive features for recognition of hypersensitive sites of regulatory genomic sequences with an evolutionary algorithm. GECCO 2010: 179-186
2000 – 2009
- 2009
- [c2]Sarah M. Richardson, Brian S. Olson, Jessica S. Dymond, Randal C. Burns, Srinivasan Chandrasegaran, Jef D. Boeke, Amarda Shehu, Joel S. Bader:
Automated Design of Assemblable, Modular, Synthetic Chromosomes. PPAM (2) 2009: 280-289 - [c1]Amarda Shehu:
An Ab-initio tree-based exploration to enhance sampling of low-energy protein conformations. Robotics: Science and Systems 2009 - 2007
- [j1]Amarda Shehu, Cecilia Clementi, Lydia E. Kavraki:
Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins. Algorithmica 48(4): 303-327 (2007)
Coauthor Index
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