Khalique Newaz
Ph.D. Student
Deparment of Computer Science and Engineering
University of Notre Dame
As of August 2018, I am a fourth year Ph.D. student in the Department of Computer Science and Engineering at the University of Notre Dame. I am working with Dr. Tijana Milenkovic.
I completed my M.Tech. in Computer science from IIIT Delhi, where I worked with Dr. Debajyoti Bera and Dr. K. Sriram.
Research
I am interested in developing and using network-based methods to study and understand biological phenomena.
Publications
Khalique Newaz, Gabriel Wright, Jacob Piland, Jun Li, Patricia L. Clark, Scott J. Emrich, and Tijana Milenkovic, Network analysis of synonymous codon usage, under review.
Khalique Newaz and Tijana Milenkovic, Improving inference of the dynamic biological network underlying aging via network propagation, under review.
Khalique Newaz†, Arash Rahnama†, Mahbooobeh Ghalehnovi, Panos J. Antsaklis, and Tijana Milenkovic, Network-based protein structural classification, under review.
Fazle E. Faisal†, Khalique Newaz†, Julie L. Chaney, Jun Li, Scott J. Emrich, Patricia L. Clark, and Tijana Milenkovic (2017), GRAFENE: Graphlet-based alignment-free network approach integrates 3D structural and sequence (residue order) data to improve protein structural comparison, Scientific Reports
Khalique Newaz, K. Sriram, Debajyoti Bera (2015), Identification of Major Signaling Pathways in Prion Disease Progression Using Network Analysis, PLoS One
† Equal contributions
Book chapter
Khalique Newaz and Tijana Milenkovic, Graphlets in Network Science and Computational Biology, a chapter in Analyzing Network Data in Biology and Medicine, edited by Natasa Przulj, Cambridge University Press, to appear, 2019.
Talks
GRAFENE: Graphlet-based alignment-free network approach integrates 3D structural and sequence (residue order) data to improve protein structural comparison
F. E. Faisal, K. Newaz, J. L. Chaney, J. Li, S. J. Emrich, P. L. Clark, and T. Milenkovic. Here are the slides and the talk.
- Presented at the workshop: BIOKDD, KDD 2018.
Network approach integrates 3D structural and sequence data to improve protein structural comparison
K. Newaz, F. E. Faisal, J. L. Chaney, J. Li, S. J. Emrich, P. L. Clark, and T. Milenkovic. Here are the slides and the talk.
- Presented at the COSI-3DSIG: Structural Bioinformatics and Computational Biophysics, ISMB 2018.
Network-based protein structural classification
A. Rahnama, K. Newaz, P. Antsaklis and T. Milenkovic. Here are the slides.
- Presented at the satellite: Machine learning in network science, NETSCI 2018.
Inference of the dynamic protein-protein interaction network in the context of aging
K. Newaz and T. Milenkovic. Here are the slides.
- Presented at the satellite: Network medicine, NETSCI 2017.
Poster presentations
GRAFENE: Graphlet-based alignment-free network approach integrates 3D structural and sequence (residue order) data to improve protein structural comparison
F. E. Faisal, K. Newaz, J. L. Chaney, J. Li, S. J. Emrich, P. L. Clark, and T. Milenkovic. Here is the poster.
- Presented at the BIOKDD and KDD 2018.
Network approach integrates 3D structural and sequence data to improve protein structural comparison
F. E. Faisal, J. L. Chaney, K. Newaz, J. Li, S. J. Emrich, P. L. Clark, and T. Milenkovic. Here is the poster.
- Presented at the ISMB 2018, NETSCI 2018, ISMB 2017, NETSCI 2017, and GLBIO 2017.
Evaluation of data integrative approaches for network inference
K. Newaz and T. Milenkovic. Here is the poster.
- Presented at the ISMB 2016.