Prof. Dr. Hesham H. Ali

Hesham H. Ali is a Professor of Computer Science and the Lee and Wilma Seaman Distinguished Dean of the College of information science and Technology (IS&T), at the University of Nebraska at Omaha (UNO). He currently serves as the director of the UNO Bioinformatics Core Facility that supports a large number of biomedical research projects in Nebraska. He has published numerous articles in various IT areas including scheduling, distributed systems, data analytics, wireless networks, and Bioinformatics. He has also published two books in scheduling and graph algorithms, and several book chapters in Bioinformatics. He is currently serving as the PI or Co-PI of several projects funded by NSF, NIH and Nebraska Research Initiative (NRI) in the areas of data analytics, wireless networks and Bioinformatics. He has been leading a Research Group at UNO that focuses on developing innovative computational approaches to classify biological organisms and analyze big bioinformatics data. The research group is currently developing several next generation data analysis tools for mining various types of large-scale biological data. This includes the development of new graph theoretic models for assembling short reads obtained from high throughput instruments, as well as employing a novel correlation networks approach for analyzing large heterogeneous biological data associated with various biomedical research areas, particularly projects associated with aging and infectious diseases. He has also been leading two funded projects for developing secure and energy-aware wireless infrastructure to address tracking and monitoring problems in medical environments, particularly to study mobility profiling for healthcare research.

KEY REFERENCES
1. J. Sommer and H. Ali, “Graph-based Analysis of Genetic Features associated with Mobile Elements in Crohn’s Disease and Healthy Gut Microbiomes,” The 8th Int Conference on Bioinformatics Models, Methods, and Algorithms (Bioinformatics 2017), Porto, Portugal. February 21-23, 2017.
2. S. Pawaskar and H. Ali, “A Dynamic Run-Profile Energy-Aware Approach for Scheduling Computationally Intensive Applications,” The 14th International Conference on High Performance Computing and Simulation (HPCS 2016), Innsbruck, Austria, July 18-22, 2016.
3. J. Sommer and H. Ali, “Graph Mining for Next Generation Sequencing: Leveraging the Assembly Graph for Biological Insights,” BMC Genomics 17 (1):340, 2016.
4. S. West and H. Ali, “On the Impact of Granularity in Extracting Knowledge from Bioinformatics Data,” The 7th International Conference on Bioinformatics Models, Methods, and Algorithms (Bioinformatics 2016), Rome, Italy. February 22-25, 2016.
5. J. Sommer, I. Thapa, and H. Ali, “Next Generation Sequence Assembler Mis-assembly of Linear Phage Genomes with Terminal Redundancy,” The 2015 Int Workshop on Computational Methods for Analyzing Metagenomics Data, held in IEEE BIBM 2015, Washington DC, Nov 9-12, 2015.
6. H. Perez-Sanchez, A. Fassihi, J. Cecillia, H. Ali and M. Cannataro, “Applications of High Performance Computing in Bioinformatics, Computational Biology and Computational Chemistry,” The 3rd Int Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2015), Granada, Spain, April 2015.
7. K. Cooper, S. Bonasera and H. Ali, “Identifying Aging Genes in the Aging Mouse Hypothalamus Using Gateway Node Analysis of Correlation Networks,” 6th Int Conf on Bioinformatics Models, Methods, and Algorithms (Bioinformatics 2015), Lisbon, Portugal. March 2015, Best Paper Awardee.
8. A. Karpate and H. Ali. A Multi-Stage Graph Approach for Efficient Clustering in Self-Organized Wireless Sensor Networks. The 2015 International Conference on Sensor Networks, (Sensornets 2015), ESEO, Angers, Loire Valley, France, Feb 11-13, 2015.
9. K. Dempsey and H. Ali. Identifying aging-related genes in mouse hippocampus using gateway nodes. BMC Systems Biology, 05/2014; 8(1):62. DOI: 10.1186/1752-0509-8-62.
10. K. Dempsey and H. Ali. On the Robustness of the Biological Correlation Network Model. The 5th International Conference on Bioinformatics Models, Methods, and Algorithms (Bioinformatics 2014). March 3-6, 2014: Angers, France.
11. J. Banwait, H. Ali, D. Bastola, “Optimization of miRNA-mRNA relationship prediction using biological features,” The international Journal of Computational Biology and Drug Design, 7(1):45-60, January 2014.
12. K. Dempsey, V. Ufimtsev, S. Bhowmick, H. Ali. A parallel template for implementing filters for biological correlation networks. International Journal of Computing 2013; 12(3):1-2.
13. Sonja Rocha-Sanchez, Laura Scheetz, Sabrina Siddiqi, Michael Weston, Lynette Smith, Kate Dempsey, Hesham Ali, JoAnn McGee, Edward Walsh. Lack of Rbl1/p107 Effects on Cell Proliferation and Maturation in the Inner Ear. Cell & Developmental Biology 2013; 2(2). DOI:10.4172/2168-9296.1000119
14. K. Dempsey and H. Ali. On the Discovery of Cellular Subsystems in Correlation Networks using Centrality Measures. Current Bioinformatics 2012; 8(3):305-314.
15. O. Bonham-Carter, H. Ali, D. Bastola, “A base composition analysis of natural patterns for the pre-processing of metagenome sequences,” BMC Bioinformatics 14:11-S5, 2013.
16. J. Warnke and H. Ali, “An efficient and scalable graph modeling approach for capturing various levels of information in next generation sequencing reads,” BMC Bioinformatics, Volume 14 Supplement 8, 2013.
17. K. Dempsey, I. Thapa, D. Bastola, and H. Ali “On Mining Biological Signals using Correlation Networks,” The Third International Workshop on Data Mining in Networks (DaMNet), held in conjunction with ICDM 2013, Dallas, Dec 7-10, 2013.
18. R. Khazanchi, K. Dempsey, I. Thapa, and H. Ali “On Identifying and Analyzing Significant Nodes in Protein-Protein Interaction Networks," The Third International Workshop on Data Mining in Networks (DaMNet), held in conjunction with ICDM 2013, Dallas, Dec 7-10, 2013.
19. K. Dempsey, I. Thapa, D. Bastola, and H. Ali. Functional Identification in Correlation Networks using Gene Ontology Edge Annotation. Accepted for publication in International Journal of Computational Biology and Drug Design (IJCBDD), 5(3-4): 222-44. (PMID: 23013651), 2012.
20. Hutter Saunders, J.A., Estes, K.A., Kosloski, L.M., Allen, H.E., Dempsey, K.M., Torres- Russotto, D.R., Meza, J.L., Santamaria, P.M., Bertoni, J.M., Murman, D.L., Ali, H.H., Standeart, D.G., Mosley, R.L., Gendelman, H.E. CD4+ Regulatory and Effector/Memory T Cell Subsets Profile Motor Dysfunction in Parkinson’s Disease. J. Neuroimmune Pharmacol. Dec;7(4):927-38. Epub 2012.
21. J. Banwait JK, H. Ali, D. Bastola. Enriching miRNA binding site specificity with sequence profile based filtering of 3'-UTR region of mRNA. The 2012 IEEE International Conference on Bioinformatics and Biomedicine, Philadelphia, PA, October 4-7, 2012.
22. K. Dempsey, S. Bhowmick, T. Chen, S. Bhowmick, H. Ali. On the Design of Advanced Filters for Biological Networks using Graph Theoretic Properties. The 2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2012), Philadelphia, PA, Oct 4-7, 2012.
23. K. Dempsey, S. Bhowmick, and H. Ali. Function-preserving filters for sampling in biological networks. 2012 Int. Conference on Computational Science (ICCS 2012), Omaha, NE, June 4-6, 2012.
24. K. Dempsey, K. Duraisamy, S. Bhowmick, and H. Ali. The Development of Parallel Adaptive Sampling Algorithms for Analyzing Biological Networks. 11th IEEE International Workshop on High Performance Computational Biology (HiCOMB 2012). May 21, 2012: Shanghai, China.
25. K. Dempsey, H. Ali, “Evaluation of Essential Genes in Correlation Networks using Measures of Centrality. 4th Annual 2011 BIBM Workshop on Biomolecular Network Analysis, Atlanta, Georgia, November 12-15, 2011.
26. H. Geng, J. Iqbal, W. Chan, H Ali. Virtual CGH: an integrative approach to predict genetic abnormalities from gene expression microarray data applied in lymphoma BMC Medical Genomics, 4:32, April 2011.
27. K. Dempsey, B. Currall, R. Hallworth and H. Ali, “A New Approach for Sequence Analysis: Illustrating an Expanded Bioinformatics View through Exploring Properties of the Prestin Protein,” a book chapter in, “Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications,” IGI Global, 2011.
28. R. Sengupta, D. Bastola and H. Ali, “Classification and Identification of Fungal Sequences Using Characteristic Restriction Endonuclease Cut Order,” Journal of Bioinformatics and Computational Biology, Volume 8, Number 6, 2010.
29. D. Quest and H. Ali, “The Motif Tool Assessment Platform (MTAP) for Sequence-Based Transcription Factor Binding Site Prediction Tools,” a Book Chapter in,” Computational Biology of Transcription Factor Binding: Methods and Protocols,” Springer, 2010.