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Publications | click on paper title for links to the full paper

2023

Lauren M Sanders, Jason H Yang, Ryan T Scott, Amina Ann Qutub, Hector Garcia Martin, Daniel C Berrios, Jaden JA Hastings, Jon Rask, Graham Mackintosh, Adrienne L Hoarfrost, Stuart Chalk, John Kalantari, Kia Khezeli, Erik L Antonsen, Joel Babdor, Richard Barker, Sergio E Baranzini, Afshin Beheshti, Guillermo M Delgado-Aparicio, Benjamin S Glicksberg, Casey S Greene, Melissa Haendel, Arif A Hamid, Philip Heller, Daniel Jamieson, Katelyn J Jarvis, Svetlana V Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E Mason, Mona Matar, George I Mias, Jack Miller, Jerry G Myers Jr, Charlotte Nelson, Jonathan Oribello, Seung-min Park, Patricia Parsons-Wingerter, RK Prabhu, Robert J Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, Corey A Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V Costes. Biological research and self-driving labs in deep space supported by artificial intelligence, Nature Machine Learning, 2023, 5: 208–219.

Ryan T Scott, Erik L Antonsen, Lauren M Sanders, Jaden JA Hastings, Seung-min Park, Graham Mackintosh, Robert J Reynolds, Adrienne L Hoarfrost, Aenor Sawyer, Casey S Greene, Benjamin S Glicksberg, Corey A Theriot, Daniel C Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E Baranzini, Afshin Beheshti, Stuart Chalk, Guillermo M Delgado-Aparicio, Melissa Haendel, Arif A Hamid, Philip Heller, Daniel Jamieson, Katelyn J Jarvis, John Kalantari, Kia Khezeli, Svetlana V Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Hector Garcia Martin, Christopher E Mason, Mona Matar, George I Mias, Jerry G Myers Jr, Charlotte Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, RK Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H Yang, Marinka Zitnik, Sylvain V Costes. Biomonitoring, Artificial Intelligence, and Precision Space Health, Nature Machine Learning, 2023, 5:196–207.

Leslie Neely, Sakiko Oyama, Guenevere Chen, Amina Qutub, Chen Chen. Lessons Learned for Behavior Analysts from Data Scientists. Perspectives on Behavior Science, 2023, in press. 

A.S. Mahadevan, N. Grandel, A. Ligeralde, J.T. Robinson, K. Francis, A.A. Qutub, Living Neural Networks: Dynamic Network Analysis of Developing Neural Progenitor Cells. bioRxiv 055533

E.P. Pollet, A. Sathish, Z. Maloney, B.L. Long, J. Brethen, A.A. Qutub, Health Signatures During COVID-19: A Precision Fitness Case Study. medRxiv 10.1101/2020.12.07

C.W. Hu, A.J. Bisberg, A.A. Qutub, Visually Guided Clustering in Biowheel: An Integration of Semi-Supervised Clustering with Interactive Visualization. bioRxiv 099739

2022

A.S. Mahadevan, B.L. Long, C.W. Hu, D.T. Ryan, N.E. Grandel, G.L. Britton, M. Bustos, M. Gonzalez Porras, K. Stojkova, A. Ligeralde, H. Son, J. Shannonhouse, J.T. Robinson, A. Warmflash, E. Brey, Y.S. Kim, A.A. Qutub, cytoNet: Network Analysis of Cell Communities. PLOS Computational Biology, 2022, 6: e1009846.

F.W. Hoff, A.D. van Dijk, Y.H. Qiu, C.W. Hu, R.E. Ries, A.C. Ligeralde, G.N. Jenkins, R.B. Gerbing, A.S. Gamis, R. Aplenc, E.A. Kolb, T.A. Alonz, S. Meshinchi, A.A. Qutub, E.S.J.M. de Bont, T.M. Horton, S.M. Kornblau, Clinical Relevance of Proteomic Profiling in De Novo Pediatric Acute Myeloid Leukemia: A Children’s Oncology Group study, Haematologiaca, 2022, 107: 2329-2343

R.I. Han, C.W. Hu, D.S. Loose, L. Yang, L. Li, J.P. Connell, M.J. Reardon, G.M. Lawrie, A.A. Qutub, J.D. Morrisett, K.J. Grande-Allen (2021) Differential proteome profile, biological pathways, and network relationships of osteogenic proteins in calcified human aortic valves. Hearts & Vessels: 1-12.

2021

2021

2022

H.A. Abbas, V. Mohanty, R. Wang, Y. Huang, S. Liang, F. Wang, J. Zhang, Y.H. Qiu, C.W. Hu, A.A. Qutub, N. Daver, M. Konopleva, A. Futreal, K. Chen, L. Wang, S.M. Kornblau (2021) Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated with Outcomes, Frontiers in Oncology 11: 2896.

M. Gonzalez Porras, K. Stojkova, M.K. Vaicik, A. Pellowe, A. Goddi, A. Carmona, B. Long, A.A. Qutub, R.N. Cohen, A. Gonzalez, E. Brey (2021) Integrins and extracellular matrix proteins module adipocyte thermogenic capacity. Scientific Reports 11: 1-14.

2019

2019

C.W. Hu, Y.H. Qiu, A. Ligeralde, A.Y. Raybon, S.Y. Yoo, K.R. Coombes, A.A. Qutub+, S.M. Kornblau+, +co-senior authors (2019) Quantifying Proteomic Heterogeneities and Hallmarks in Acute Myelogenous Leukaemia, Nature Biomedical Engineering 3: 889-901. 

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G. Britton, I. Heemskerk, R. Hodge, A.A. Qutub, A. Warmflash (2019) A Novel Self-Organizing Embryonic Stem Cell System Reveals Signaling Logic Underlying the Patterning of Human Ectoderm. Development, 2019, 146: dev179093

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T.T. Tang, J. Zawaski, K. Francis, A.A. Qutub, M.W. Gaber (2019) Image-based Classification of Tumor Type and Growth Rate using Machine Learning: a preclinical study, Scientific Reports 9: 12529.

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P.P. Ruvolo, C.W. Hu, Y.H. Qu, K.R. Coombes, M. Andreeff, A.A. Qutub, S.M. Kornblau (2019) Galectin 3 is connected to CD74 in a previously unknown protein network that is associated with poor survival in patients with AML, EBioMedicine 44: 126–137. 

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F.W. Hoff, C.W. Hu, A.A. Qutub, Y. Qiu, M.J. Hornbaker, C. Bueso-Ramos, H.A. Abbas, S.M. Post, E.S.J.M., de Bont, S.M. Kornblau (2019) Proteomic Profiling of Acute Promyelocytic Leukemia Identifies Two Protein Signatures Associated with Relapse. Proteomics – Clinical Applications 16: e1800133.

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F. Hoff, C.W. Hu, Y.H. Qiu, A. Ligeralde, E. de Bont, S.Y. Yoo, A.A. Qutub, T. Horton, S.M. Kornblau (2018) Recurrent Patterns of Protein Expression Signatures in Pediatric Acute Lymphoblastic Leukemia (ALL): Recognition and Therapeutic Guidance, Molecular Cancer Research 16: 1263-1274.

 

F. Hoff, C.W. Hu, Y.H. Qiu, S.Y. Yoo, E. de Bont, H. Mahmud, A.A. Qutub, T. Horton, S.M. Kornblau (2018) Recognition of Recurrent Protein Expression Patterns in Pediatric Acute Myeloid Leukemia (AML) Suggest New Therapeutic Targets, Molecular Cancer Research 16: 1275-1286.

 

E.O. Kaynak, A.A. Qutub, O.Y. Celiktas (2018) Advances in Glioblastoma Multiforme Treatment: New Models for Nanoparticle Therapy, Frontiers in Physiology 9: 170.

 

A.D. van Dijk, C.W. Hu, E.S.J.M. de Bont, Y.H. Qiu, F.W. Hoff, S.Y. Yoo, K.R. Coombes, A.A. Qutub, S.M. Kornblau (2018) Histone Modification Patterns using RPPA-based Profiling Predict Outcome in Acute Myeloid Leukemia Patients, Proteomics 18: e1700379.

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F.W. Hoff, C.W. Hu, A.A. Qutub, Y. Qiu, E. Graver, G. Hoang, M. Chauhan, E.S.J.M. de Bont, S.M. Kornblau (2018) Mycoplasma contamination of leukemic cell lines alters protein expression determined by reverse phase protein arrays. Cytotechnology 70: 1529-1535.

 

C.W. Hu, H. Li, A.A. Qutub (2018) Shrinkage Clustering: A Fast and Size-Constrained Algorithm for Biomedical Applications, BMC Bioinformatics 19: 19.

 

C. Lantos, S.M. Kornblau, A.A. Qutub (2018) Quantitative Morphological and Cytological Analyses in Leukemia. In: Hematology: Latest Research & Clinical Advances.

 

C.W. Hu, A.A. Qutub (2018) Proteomics in Acute Myeloid Leukemia. In: Myeloid Leukemia.

2018

2018

2017
2016

L. Liu, Y. Chang, T. Yang, D.P. Noren, B.L. Long, S.M. Kornblau, A.A. Qutub, J. Ye (2016) Evolution-Informed Modeling Improves Outcome Prediction for Cancers, Evolutionary Applications, 10: 68-76. (PDF)

 

C.W. Hu, A.A. Qutub (2016) progenyClust: an R package for Progeny Clustering, The R Journal, in press.

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D.P. Noren, B. Long, R. Norel, K. Rhrissorrakrai, K. Hess, C.W. Hu, A. Bisberg, A. Schultz, E. Engquist, L. Liu, E. Lin, G. Chen, H. Xie, G. Hunter, AML DREAM Consortium, T. Norman, S. Friend, G.B. Mills, G. Stolovitzky, S.M. Kornblau, A.A. Qutub (2016) A Crowd Sourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis, PLOS Computational Biology, 12:e1004890. (PDF)

 

A. Schultz, A.A. Qutub (2016) Reconstruction of Tissue-Specific Metabolic Networks Using CORDA, PLOS Computational Biology, 12(3).

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D.P. Noren, W.H. Chou, S.H. Lee, A.A. Qutub, A. Warmflash, D.S. Wagner, A.S. Popel, A. Levchenko (2016) Endothelial cells decode VEGF-mediated Ca2+ signaling patterns to produce distinct functional responses, Science Signaling 9: ra20. 

 

S.M. Hill, L. Heiser, T. Cokelear, M. Unger, D. Carlin, Y. Zhang, A. Sokolov, E. Paul, C.K. Wong, K. Graim, A. Bivol, H. Wang, F. Zhu, B. Afsari, L.V. Danilova, A.V. Favorov, W.S. Lee, D. Taylor, C.W. Hu, D.P. Noren, B.L. Long, A.J. Bisberg, HPN-DREAM Consortium, G.B. Mills, J.W. Gray, M. Kellen, T. Norman, S. Friend, A.A. Qutub, E.J. Fertig, Y. Guan, M. Song, J. Stuart, H. Koeppl, P.T. Spellman, G. Stolovitzky, J.S.-Rodriguez, S. Mukherjee (2016) Empirical Assessment of Causal Network Inference through A Community-Based Effort, Nature Methods, 13: 310-318. (Interactive DREAM 8 Breast Cancer Data Portal; Highlights Biowheel)

C.W. Hu, S.M. Kornblau, J.H. Slater, A.A. Qutub (2015) Progeny Clustering: A Method to Identify Biological Phenotypes, Scientific Reports 5: 12894. (R package available; Highlighted in Health Data Management) (PDF)

 

J.H. Slater, J.C. Culver, B. Long, C.W. Hu, J. Hu, T. Birk, A.A. Qutub, M.E. Dickinson, J.L. West (2015) Recapitulation of the Cellular Architecture of a User-Chosen Cell-of-Interest Using Cell-Derived, Biomimetic Patterning, ACS Nano, 9: 6128–6138. 

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K.W. Lin, A. Liao, A.A. Qutub (2015) Simulation Predicts IGFBP2-HIF1 Signaling Drives Glioblastoma Growth, PloS Computational Biology, 11: e1004169. 

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A. Schultz, A.A. Qutub (2015) Predicting Internal Cell Fluxes at Sub-Optimal Growth, BMC Systems Biology, 9:18. 

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R. Rekhi, D. Ryan, B. Zaunbrecher, C.W. Hu, A.A. Qutub (2015) Computational Cell Phenotyping in the Lab, Plant and Clinic. In: Computational Bioengineering. (Zhang G, ed.), CRC Press, pp. 265-292.

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A.A. Qutub, A.S. Popel (2015) Angiogenesis: Mathematical and Computational Modeling, Encyclopedia of Applied and Computational Mathematics. (B. Engquist, ed.), Springer, pp 58-67.

D.P. Noren, R. Rekhi, B.L. Long, A.A. Qutub (2014) Multiscale Models of Angiogenesis. In: Vascularization: Regenerative Medicine and Tissue Engineering. (E. Brey, ed.), CRC Press, pp. 213-234.

 

R. Rekhi, A.A. Qutub (2013) Systems Biology Approaches for Synthetic Biology: A Pathway Towards Mammalian Design, Frontiers in Computational Physiology and Medicine 4: 285.

 

S.M. Kornblau, A.A. Qutub, H. Yao, H. York, Y. Qiu, D. Graber, F. Ravandi, J. Cortes, M. Andreeff, N. Zhang, K.R. Coombes (2013) Proteomic Profiling Identifies Distinct Protein Patterns in Acute Myelogenous Leukemia CD34+CD38- Stem-Like Cells, PLoS One, 8: e78453.

 

D. Ryan, J. Hu, B. Zaunbrecher, B. Long, A.A. Qutub (2013) Predicting Endothelial Cell Phenotypes in Angiogenesis. Proceedings of the ASME 2013: Global Congress on NanoEngineering for Medicine and Biology 93124: 13-20.

 

B. Long, R. Rekhi, J. Jung, A. Abrego, A.A. Qutub (2013) Cells as State Machines: Cell Behavior Patterns Arise during Capillary Formation as a Function of BDNF and VEGF, Journal of Theoretical Biology, 326: 43-57. (PDF)

 

R. Schweller, J. Zimak, A.A. Qutub, Hittleman W.N., Diehl M.R. (2012) Multiplexed In Situ Immunofluorescence via Dynamic DNA Complexes. Angewandte Chemie 51: 9292-9296. (Link)

 

H. York, S.M. Kornblau, A.A. Qutub (2012) Network Analysis of Reverse Phase Protein Expression Data: Characterizing Protein Signatures in Acute Myeloid Leukemia Cytogenetic Categories t(8;21) and inv(16), Proteomics 12: 2084-2093.(Link)

 

M.O. Stefaninni, A.A. Qutub, F. Mac Gabhann, A.S. Popel (2012) Computational Models of VEGF-Associated Angiogenic Processes in Cancer. Math Med Biol 29: 85-94.

 

S.M. Kornblau, Y.H. Qiu, N. Zhang, N. Singh, S. Faderl, A. Ferrajoli, H. York, A.A. Qutub, K.R. Coombes, D.K. Watson (2011) Abnormal Expression of Friend Leukemia Virus Integration 1 (FLI1) Protein Is an Adverse Prognostic Factor in Acute Myeloid Leukemia, Blood 118: 5604-5612.

 

G. Liu, A.A. Qutub, P. Vempati, F. Mac Gabhann, A.S. Popel (2011) Module-Based Multiscale Simulation of Angiogenesis in Skeletal Muscle, Theoretical Biology & Medical Modelling 8: 6.

 

J.C. Nathan, A.A. Qutub (2010) “Patient-Specific Modeling of Hypoxic Response and Microvasculature Dynamics.” In: “Patient-Specific Modeling of the Cardiovascular System.” Roy Kerckhoffs (ed.). Springer, pp.183-201.

 

F. Mac Gabhann, A.A. Qutub, B.H. Annex, A.S. Popel (2010) “Systems Biology of Proangiogenic Therapeutic Strategies targeting the VEGF system.” Wiley Interdisciplinary Reviews: Systems Biology and Medicine 2: 694-707.

 

A.A. Qutub, F. Mac Gabhann, E.D. Karagiannis, A.S. Popel (2010) “Modeling Angiogenesis In Silico: From Nanoscale to Organ System.” In: “Multiscale Modeling of Particle Interactions: Applications in Biology and Nanotechnology.” Michael R. King and David J. Gee (eds.). Wiley, pp. 287-320.

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A.A. Qutub, A.S. Popel (2009) Cell Elongation, Proliferation & Migration Differentiate Endothelial Cell Phenotypes and Determine Capillary Sprouting, BMC System Biology 3.

 

A.A. Qutub, F. Mac Gabhann, E.D. Karagiannis, P. Vempati, A.S. Popel (2009) Multiscale Molecular-Based Models of Angiogenesis, IEEE Engineering in Medicine & Biology 28: 14-31.

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A.A. Qutub, G. Liu, P. Vempati, A.S. Popel (2009) Integration of Angiogenesis Modules at Multiple Scales: From Molecular to Tissue. Pacific Symposium on Biocomputing 14: 316-327.

 

A.A. Qutub, A.S. Popel (2008) Reactive Oxygen Species Regulate HIF1a Differentially in Cancer and Ischemia, Molecular and Cellular Biology 28: 5106-5119.

 

A.A. Qutub, A.S. Popel (2007) Three Autocrine Feedback Loops Determine HIF1a Expression in Chronic Hypoxia, BBA – Molecular Cell Research 1773: 1511-1525.

 

A.A. Qutub, A.S. Popel (2006) A Computational Model of Intracellular Oxygen Sensing by Hypoxia-Inducible Factor HIF1a, Journal of Cell Science 119: 3467-3480.

 

A.A. Qutub, C.A. Hunt (2005) Glucose Transport to the Brain: A Systems Model. Brain Res Rev 49: 595-617.

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