Thirty biologically interpretable clusters of transcription factors distinguish cancer type von Abrams, Zachary B, Zucker, Mark, Wang, Min, Asiaee Taheri, Amir, Abruzzo, Lynne V, Coombes, Kevin R

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A framework for ontology-based question answering with application to parasite immunology von Asiaee, Amir H, Minning, Todd, Doshi, Prashant, Tarleton, Rick L

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SITH: An R package for visualizing and analyzing a spatial model of intratumor heterogeneity von Nicol, Phillip B., Barabási, Dániel L., Coombes, Kevin R., Asiaee, Amir

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Oncogenetic network estimation with disjunctive Bayesian networks von Nicol, Phillip B., Coombes, Kevin R., Deaver, Courtney, Chkrebtii, Oksana, Paul, Subhadeep, Toland, Amanda E., Asiaee, Amir

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A semantic problem solving environment for integrative parasite research: identification of intervention targets for Trypanosoma cruzi von Parikh, Priti P, Minning, Todd A, Nguyen, Vinh, Lalithsena, Sarasi, Asiaee, Amir H, Sahoo, Satya S, Doshi, Prashant, Tarleton, Rick, Sheth, Amit P

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Elastic Statistical Shape Analysis of Biological Structures with Case Studies: A Tutorial von Cho, Min Ho, Asiaee, Amir, Kurtek, Sebastian

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Explaining Gene Expression Using Twenty-One MicroRNAs von Asiaee, Amir, Abrams, Zachary B, Nakayiza, Samantha, Sampath, Deepa, Coombes, Kevin R

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Leveraging Observational Data for Efficient CATE Estimation in Randomized Controlled Trials von Asiaee, Amir, Di Gravio, Chiara, Mei, Yuting, Huling, Jared D

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High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient von Asiaee, Amir, Samet Oymak, Coombes, Kevin R, Banerjee, Arindam

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Leveraging Observational Data for Efficient CATE Estimation in Randomized Controlled Trials von Asiaee, Amir, Chiara Di Gravio, Mei, Yuting, Huling, Jared D

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Time Series Deinterleaving of DNS Traffic von Asiaee, Amir, Goel, Hardik, Ghosh, Shalini, Yegneswaran, Vinod, Banerjee, Arindam

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High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient von Asiaee, Amir, Oymak, Samet, Coombes, Kevin R, Banerjee, Arindam

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From Questions to Effective Answers: On the Utility of Knowledge-Driven Querying Systems for Life Sciences Data von Asiaee, Amir H., Doshi, Prashant, Minning, Todd, Sahoo, Satya, Parikh, Priti, Sheth, Amit, Tarleton, Rick L.

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Revisiting Non-Progressive Influence Models: Scalable Influence Maximization von Golnari, Golshan, Asiaee, Amir, Banerjee, Arindam, Zhang, Zhi-Li

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Time Series Deinterleaving of DNS Traffic von Asiaee, Amir, Goel, Hardik, Ghosh, Shalini, Yegneswaran, Vinod, Banerjee, Arindam

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Revisiting Non-Progressive Influence Models: Scalable Influence Maximization von Golshan Golnari, Asiaee, Amir, Banerjee, Arindam, Zhi-Li, Zhang

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From Questions to Effective Answers: On the Utility of Knowledge-Driven Querying Systems for Life Sciences Data von Asiaee, Amir H, Doshi, Prashant, Minning, Todd, Sahoo, Satya, Parikh, Priti, Sheth, Amit, Tarleton, Rick L

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From Questions to Effective Answers: On the Utility of Knowledge-Driven Querying Systems for Life Sciences Data von Asiaee, Amir H, Doshi, Prashant, Minning, Todd, Sahoo, Satya, Parikh, Priti, Sheth, Amit, Tarleton, Rick L

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Additional file 2 of Thirty biologically interpretable clusters of transcription factors distinguish cancer type von Abrams, Zachary B., Zucker, Mark, Wang, Min, Asiaee Taheri, Amir, V. Abruzzo, Lynne, R. Coombes, Kevin

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Additional file 3 of Thirty biologically interpretable clusters of transcription factors distinguish cancer type von Abrams, Zachary B., Zucker, Mark, Wang, Min, Asiaee Taheri, Amir, V. Abruzzo, Lynne, R. Coombes, Kevin

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