Research articles, presentations, and other scholarship

Recent Submissions

  • Impossibility of coin flipping in generalized probabilistic theories via discretizations of semi-infinite programs 

    Sikora, Jamie; Selby, John H. (2020-10-23)
    Coin flipping is a fundamental cryptographic task where spatially separated Alice and Bob wish to generate a fair coin flip over a communication channel. It is known that ideal coin flipping is impossible in both classical ...
  • A feasibility study to use machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differential absorption spectroscopy measurements 

    Dong, Yun; Spinei, Elena; Karpatne, Anuj (2020-10-16)
    In this study, we explore a new approach based on machine learning (ML) for deriving aerosol extinction coefficient profiles, single-scattering albedo and asymmetry parameter at 360 nm from a single multi-axis differential ...
  • A Classifier to Detect Informational vs. Non-Informational Heart Attack Tweets 

    Karajeh, Ola; Darweesh, Dirar; Darwish, Omar; Abu-El-Rub, Noor; Alsinglawi, Belal; Alsaedi, Nasser (MDPI, 2021-01-16)
    Social media sites are considered one of the most important sources of data in many fields, such as health, education, and politics. While surveys provide explicit answers to specific questions, posts in social media have ...
  • Multiple Myeloma DREAM Challenge reveals epigenetic regulator PHF19 as marker of aggressive disease 

    Mason, Mike J.; Schinke, Carolina; Eng, Christine L. P.; Towfic, Fadi; Gruber, Fred; Dervan, Andrew; White, Brian S.; Pratapa, Aditya; Guan, Yuanfang; Chen, Hongjie; Cui, Yi; Li, Bailiang; Yu, Thomas; Chaibub Neto, Elias; Mavrommatis, Konstantinos; Ortiz, Maria; Lyzogubov, Valeriy; Bisht, Kamlesh; Dai, Hongyue Y.; Schmitz, Frank; Flynt, Erin; Rozelle, Dan; Danziger, Samuel A.; Ratushny, Alexander; Dalton, William S.; Goldschmidt, Hartmut; Avet-Loiseau, Herve; Samur, Mehmet; Hayete, Boris; Sonneveld, Pieter; Shain, Kenneth H.; Munshi, Nikhil; Auclair, Daniel; Hose, Dirk; Morgan, Gareth; Trotter, Matthew; Bassett, Douglas; Goke, Jonathan; Walker, Brian A.; Thakurta, Anjan; Guinney, Justin (2020-02-14)
    While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients does not benefit from current therapeutics for unclear reasons. Many gene expression-based ...
  • Predicting lake surface water phosphorus dynamics using process-guided machine learning 

    Hanson, Paul C.; Stillman, Aviah B.; Jia, Xiaowei; Karpatne, Anuj; Dugan, Hilary A.; Carey, Cayelan C.; Stachelek, Joseph; Ward, Nicole K.; Zhang, Yu; Read, Jordan S.; Kumar, Vipin (2020-08-15)
    Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing ...
  • Diagnostic interchangeability of deep convolutional neural networks reconstructed knee MR images: preliminary experience 

    Subhas, Naveen; Li, Hongyu; Yang, Mingrui; Winalski, Carl S.; Polster, Joshua; Obuchowski, Nancy; Mamoto, Kenji; Liu, Ruiying; Zhang, Chaoyi; Huang, Peizhou; Gaire, Sunil Kumar; Liang, Dong; Shen, Bowen; Xiaojuan, Li; Ying, Leslie (2020-09)
    Background: MRI acceleration using deep learning (DL) convolutional neural networks (CNNs) is a novel technique with great promise. Increasing the number of convolutional layers may allow for more accurate image reconstruction. ...
  • Collaborative behavior, performance and engagement with visual analytics tasks using mobile devices 

    Chen, Lei; Liang, Hai-Ning; Lu, Feiyu; Papangelis, Konstantinos; Man, Ka L.; Yue, Yong (2020-11-22)
    Interactive visualizations are external tools that can support users’ exploratory activities. Collaboration can bring benefits to the exploration of visual representations or visualizations. This research investigates the ...
  • Applying GIS and Text Mining Methods to Twitter Data to Explore the Spatiotemporal Patterns of Topics of Interest in Kuwait 

    G. Almatar, Muhammad; Alazmi, Huda S.; Li, Liuqing; Fox, Edward A. (MDPI, 2020-11-25)
    Researchers have developed various approaches for exploring the spatial information, temporal patterns, and Twitter content in topics of interest in order to generate a better understanding of human behavior; however, few ...
  • Large-scale protein function prediction using heterogeneous ensembles 

    Wang, Linhua; Law, Jeffrey N.; Kale, Shiv D.; Murali, T. M.; Pandey, Gaurav (F1000Research, 2018-09-28)
    Heterogeneous ensembles are an effective approach in scenarios where the ideal data type and/or individual predictor are unclear for a given problem. These ensembles have shown promise for protein function prediction (PFP), ...
  • Efficient Synthesis of Mutants Using Genetic Crosses 

    Pratapa, Aditya; Jalihal, Amogh P.; Ravi, S. S.; Murali, T. M. (2018-06-29)
    The genetic cross is a fundamental, flexible, and widely-used experimental technique to create new mutant strains from existing ones. Surprisingly, the problem of how to efficiently compute a sequence of crosses that can ...
  • The PathLinker app: Connect the dots in protein interaction networks 

    Gil, Daniel P.; Law, Jeffrey N.; Murali, T. M. (F1000Research, 2017-01-20)
    PathLinker is a graph-theoretic algorithm for reconstructing the interactions in a signaling pathway of interest. It efficiently computes multiple short paths within a background protein interaction network from the receptors ...
  • Computational prediction of host-pathogen protein–protein interactions 

    Dyer, Matthew D.; Murali, T. M.; Sobral, Bruno W. (Oxford University Press, 2007)
    Motivation: Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is ...
  • Automating the PathLinker app for Cytoscape 

    Huang, Li Jun; Law, Jeffrey N.; Murali, T. M. (F1000Research, 2018-06-12)
    PathLinker is a graph-theoretic algorithm originally developed to reconstruct the interactions in a signaling pathway of interest. It efficiently computes multiple short paths within a background protein interaction network ...
  • Accurate and Efficient Gene Function Prediction using a Multi-Bacterial Network 

    Law, Jeffrey N.; Kale, Shiv D.; Murali, T. M. (2019-05-24)
    The rapid rise in newly sequenced genomes requires the development of computational methods to supplement experimental functional annotations. The challenge that arises is to develop methods for gene function prediction ...
  • Connectivity Measures for Signaling Pathway Topologies 

    Franzese, Nicholas; Groce, Adam; Murali, T. M.; Ritz, Anna (Virginia Tech, 2019-03-30)
    Characterizing cellular responses to different extrinsic signals is an active area of research, and curated pathway databases describe these complex signaling reactions. Here, we revisit a fundamental question in signaling ...
  • Identifying Human Interactors of SARS-CoV-2 Proteins and Drug Targets for COVID-19 using Network-Based Label Propagation 

    Law, Jeffrey N.; Akers, Kyle; Tasnina, Nure; Santina, Catherine M. Della; Kshirsagar, Meghana; Klein-Seetharaman, Judith; Crovella, Mark; Rajagopalan, Padmavathy; Kasif, Simon; Murali, T. M. (Virginia Tech, 2020-06-22)
    Motivated by the critical need to identify new treatments for COVID- 19, we present a genome-scale, systems-level computational approach to prioritize drug targets based on their potential to regulate host- virus interactions ...
  • Teaching Natural Language Processing through Big Data Text Summarization with Problem-Based Learning 

    Li, Liuqing; Geissinger, Jack; Ingram, William A.; Fox, Edward A. (Sciendo, 2020)
    Natural language processing (NLP) covers a large number of topics and tasks related to data and information management, leading to a complex and challenging teaching process. Meanwhile, problem-based learning is a teaching ...
  • SBML Level 3: an extensible format for the exchange and reuse of biological models 

    Keating, Sarah M.; Waltemath, Dagmar; Koenig, Matthias; Zhang, Fengkai; Draeger, Andreas; Chaouiya, Claudine; Bergmann, Frank T.; Finney, Andrew; Gillespie, Colin S.; Helikar, Tomas; Hoops, Stefan; Malik-Sheriff, Rahuman S.; Moodie, Stuart L.; Moraru, Ion I.; Myers, Chris J.; Naldi, Aurelien; Olivier, Brett G.; Sahle, Sven; Schaff, James C.; Smith, Lucian P.; Swat, Maciej J.; Thieffry, Denis; Watanabe, Leandro; Wilkinson, Darren J.; Blinov, Michael L.; Begley, Kimberly; Faeder, James R.; Gomez, Harold F.; Hamm, Thomas M.; Inagaki, Yuichiro; Liebermeister, Wolfram; Lister, Allyson L.; Lucio, Daniel; Mjolsness, Eric; Proctor, Carole J.; Raman, Karthik; Rodriguez, Nicolas; Shaffer, Clifford A.; Shapiro, Bruce E.; Stelling, Joerg; Swainston, Neil; Tanimura, Naoki; Wagner, John; Meier-Schellersheim, Martin; Sauro, Herbert M.; Palsson, Bernhard; Bolouri, Hamid; Kitano, Hiroaki; Funahashi, Akira; Hermjakob, Henning; Doyle, John C.; Hucka, Michael (2020-08)
    Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We ...
  • Cell cycle control and environmental response by second messengers in Caulobacter crescentus 

    Xu, Chunrui; Weston, Bronson R.; Tyson, John J.; Cao, Yang (2020-09-30)
    Background Second messengers, c-di-GMP and (p)ppGpp, are vital regulatory molecules in bacteria, influencing cellular processes such as biofilm formation, transcription, virulence, quorum sensing, and proliferation. While ...
  • Crossing complexity of space-filling curves reveals entanglement of S-phase DNA 

    Kinney, Nick; Hickman, Molly; Anandakrishnan, Ramu; Garner, Harold R. (2020-08-31)
    Space-filling curves have been used for decades to study the folding principles of globular proteins, compact polymers, and chromatin. Formally, space-filling curves trace a single circuit through a set of points (x,y,z); ...

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