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Publications from Lisa Tucker-Kellogg's Group

See Auto-archive at ORCID 0000-0002-1301-7069

Modeling Synergistic, Additive, or Antagonistic Combination Effects

◊ “Combination Therapy and the Evolution of Resistance: The Theoretical Merits of Synergism and Antagonism in Cancer.” By Elysia Saputra, Lu Huang, Yihui Chen, and Lisa Tucker-Kellogg*. Cancer Research 78(9):2419-2431 (2018). (AACR)

◊ “Computational analysis reveals the coupling between bistability and the sign of a feedback loop in a TGF-β1 activation model.” By Huipeng Li, Lakshmi Venkatraman, B.C. Narmada, Jacob K. White, Hanry Yu*, Lisa Tucker-Kellogg*. BMC Systems Biology 11:136(2017). (BMC)

◊ “Wnt proteins synergize to activate β-catenin signaling.” By A Alok, Z Lei, NS Jagannathan, S Kaur, N Harmston, SG Rozen, L Tucker-Kellogg, DM Virshup. Journal of Cell Science 130(9):1532-1544. (2017). (JCS)

◊ “Computational Modeling of LY303511 and TRAIL-Induced Apoptosis Suggests Dynamic Regulation of cFLIP.” By Yuan Shi, Gregory Mellier, Sinong Huang, Jacob White, Shazib Pervaiz* , Lisa Tucker-Kellogg *. Bioinformatics 29(3): 347-354. (2013). (OxfordJournals)

◊ “The synergy in cytokine production through MyD88-TRIF pathways is co-ordinated with ERK phosphorylation in macrophages.” By RST Tan, B Lin, Q Liu, L Tucker-Kellogg, B Ho, BPL Leung, JL Ding*. Immunology and Cell Biology 91(5):377-87 (2013). (Nature)

◊ “FLIP: a Flop for Execution Signals.” By K Subramaniam, JL Hirpara, L Tucker-Kellogg, G Tucker-Kellogg, S Pervaiz* Cancer Letters, 332(2):151-5 (2012). (ScienceDirect)

◊ "Simulating EGFR-ERK Signaling Control by Scaffold Proteins KSR and MP1 Reveal Differential Ligand-Sensitivity co-regulated by Cbl-CIN85 and Endophilin." By Lu Huang, Catherine Q Pan, B Li, Lisa Tucker-Kellogg, Bruce Tidor, YZ Chen*, BC Low*. PLoS One. 2011;6(8):e22933; (2011). (PLoS)

◊ “Computational Modeling of Pathway Dynamics For Detecting Drug Effects: Paradoxical Effects of LY303511 on TRAIL-Induced Apoptosis.” By Y Shi, SM Varghese, S Huang, J White, S Pervaiz*, L Tucker-Kellogg * . Computational Systems Bioinformatics “CSB09”, 8: 213-224 (2009). (Life Sciences Society)

Modelling Injury Response

◊ “Membrane Tension Controls Lamellipodial Buckling and Adhesion Positioning at Leading Edge of Cells." By B Pontes, P Monzo, L Gole, AL Le Roux, AJ Kosmalska, ZY Tam, W Luo, S Kan, V Viasnoff, P Roca-Cusachs, L Tucker-Kellogg, and N Gauthier. Journal of Cell Biology (ePub 7 July 2017). (Rockefeller) or (PDF)

◊ "Membrane permeability during pressure ulcer formation: A computational model of dynamic competition between cytoskeletal damage and repair" by N. Suhas Jagannathan and Lisa Tucker-Kellogg*. Journal of Biomechanics 49(8):1311-1320 (2016). (PDF)

◊ “Superpixel-based segmentation of muscle fibers in multi-channel microscopy.” By BP Nguyen, H Heemskerk, PTC So and L Tucker-Kellogg. BMC Systems Biology 10 (Suppl 5): 124 (2016). BioMedCentral

◊ "Non-Canonical Activation of Akt in Serum-stimulated Fibroblasts, Revealed by Comparative Modeling of Pathway Dynamics." by Tri Hieu Nim, Le Luo, Jacob K White, Marie-Veronique Clement*, and Lisa Tucker-Kellogg*. PLoS Computational Biology 11(11): e1004505 (2015). (PLoS open access)

◊ "The Self-Limiting Dynamics of TGF-β Signaling In Silico and In Vitro, with Negative Feedback through PPM1A Upregulation." By Wang J, Tucker-Kellogg L, Ng IC, Jia R, Thiagarajan PS, White JK, Yu H. PLoS Computational Biology 10(6):e1003573 (2014). (PLoS open access)

◊ "Extracellular Hemoglobin Upregulates and Binds to Tissue Factor on Macrophages: Implications for Coagulation and Oxidative Stress." By Neha Bahl, Imelda Winarsih, Lisa Tucker-Kellogg *, Ding Jeak Ling *. Thrombosis and Haemostasis 111(1):67-78(2014). (Schattauer) or PDF

◊ "The CD47-binding Peptide of Thrombospondin-1 Induces Defenestration of Liver Sinusoidal Endothelial Cells." By L. Venkatraman and L. Tucker-Kellogg*. Liver International 33(9):1386-97 (2013). (Wiley)

◊ “Hepatic stellate cell-targeted delivery of hepatocyte growth factor transgene via bile duct infusion enhances its expression at fibrotic foci to regress dimethylnitrosamine-induced liver fibrosis.” By BC Narmada, Y Kang, L Venkatraman, Q Peng, RB Sakban, BNX Jiang, RM Bunte, PTC So, L Tucker-Kellogg, HQ Mao* & H Yu*. Human Gene Therapy 24(5):508-19 (2013). (Liebert)

◊ “HGF regulates the activation of TGF-ß1 in rat hepatocytes and hepatic stellate cells.” By BC Narmada, S-M Chia, L Tucker-Kellogg*, and H Yu.*  Journal of Cellular Physiology, 228 (2): 393-401. (2013). (ePub  June 20, 2012) (Wiley)

◊ “Plasmin Triggers a Switch-like Decrease in Thrombospondin-Dependent Activation of TGF-β1” By Lakshmi Venkatraman, Ser-Mien Chia, Balakrishnan Chakrapani Narmada, Liang Siang Poh, Huipeng Li, Rashidah Sakban, Rui Rui Jia, Shali Shen, Jacob K. White, Sourav Saha Bhowmick, C. Forbes Dewey, Jr., Peter T. So, Lisa Tucker-Kellogg * , Hanry Yu.* Biophysical Journal, 103: 1060–1068.(2012). (Cell Press)

◊ "Systems Biology in Biomaterials and Tissue Engineering.” A. Ananthanarayanan, L. Tucker-Kellogg, B.C. Narmada, L. Venkatraman, N.A. Abdul Rahim, Y. Wang, C.H. Kang, H. Yu. Comprehensive Biomaterials, Vol. 5, p.177-188 (2011). (ScienceDirect)

◊ “The Steady States and Dynamics of Urokinase-mediated Plasmin Activation, in Silico and in Vitro” By L Venkatraman, H Li, CF Dewey Jr, JK White, SS Bhowmick, H Yu *, L Tucker-Kellogg* Biophysical Journal 101:1825–1834 (2011). (Cell Press)

◊ “Predicting in vivo anti-hepatofibrotic drug efficacy based on in vitro high-content analysis” By B Zheng, L Tan, X Mo, W Yu, Y Wang, L Tucker-Kellogg, R Welsch, P So, H Yu*. PLoS One 6(11): e26230(2011). (PLoS)

◊ “Cell-Delivery Therapeutics for Liver Regeneration” By W-X Zhang, L Tucker-Kellogg (joint first author), BC Narmada, L Venkatraman, S Chang, Y Lu, H Yu*. Advanced Drug Delivery Reviews 62(7-8):814-26 (2010). (ScienceDirect)

◊ “The Steady States and Dynamics of Urokinase-Mediated Plasmin Activation” By L Venkatraman, H Yu, SS Bhowmick, CF Dewey Jr., L Tucker-Kellogg . Pacific Symposium on Biocomputing 15:190-199 (2010). (Pubmed)

Probabilistic Methods for Modeling

◊ "Development of a classification model for non-alcoholic steatohepatitis (NASH) using confocal Raman micro-spectroscopy" By J Yan, Y Yu, JW Kang, ZY Tam, S Xu, ELS Fong, SP Singh, Z Song, L Tucker-Kellogg, PTC So, H Yu. J Biophotonics (to appear) . Pubmed or Wiley Journals

◊ “SPEDRE: a Web Server for Estimating Rate Parameters of Cell Signaling Dynamics in Data-Rich Environments." By Tri Hieu Nim, Jacob K. White, Lisa Tucker-Kellogg* Nucleic Acids Research, ePub doi: 10.1093/nar/gkt459 (2013). (OxfordJournals)

◊ “Systematic Parameter Estimation in Data-Rich Environments for Cell Signaling Dynamics.” By Tri Hieu Nim, Le Luo, Marie-Véronique Clément, Jacob K. White, Lisa Tucker-Kellogg*. Bioinformatics 29(8):1044-1051(2013). (OxfordJournals)

◊ “Reactive Oxygen Species (ROS) and Sensitization to TRAIL-Induced Apoptosis, in Bayesian Network Modeling of HeLa Cell Response to LY303511.” By Lisa Tucker-Kellogg, Yuan Shi, Jacob K.White, Shazib Pervaiz. Biochemical Pharmacology, 84 (10): 1307-17 (2012). (ScienceDirect)

◊ “Predicting in vivo anti-hepatofibrotic drug efficacy based on in vitro high-content analysis” By B Zheng, L Tan, X Mo, W Yu, Y Wang, L Tucker-Kellogg, R Welsch, P So, H Yu*. PLoS One 6(11): e26230(2011). (PLoS)

◊ “Composing Globally Consistent Pathway Parameter Estimates Through Belief Propagation.” By G Koh, L Tucker-Kellogg, D Hsu and PS Thiagarajan. Proceedings of the 7th Workshop on Algorithms in Bioinformatics (WABI), Lecture Notes in Bioinformatics 4645: 420-430 (2007). (SpringerLink)

Structural Modelling

◊ "Exome Sequencing Reveals Germline SMAD9 Mutation that Reduces PTEN Expression and is Associated with Hamartomatous Polyposis and Gastrointestinal Ganglioneuromas" By Joanne Ngeow, Wanfeng Yu, Lamis Yehia, Farshad Niazi, Jinlian Chen, Xuhua Tang, Brandie Heald, Junying Lei, Todd Romigh, Lisa Tucker-Kellogg, Kiat Hon Lim, Haiwei Song, Charis Eng*. Gastroenterology 149(4): 886–889.e5 (2015). (AGAjournals) or PDF

◊ “Delineation of Lipopolysaccharide (LPS)-binding Sites on Hemoglobin: FROM IN SILICO PREDICTIONS TO BIOPHYSICAL CHARACTERIZATION.” By N Bahl, R Du, I Winarsih, B Ho, L Tucker-Kellogg, B Tidor, and JL Ding*. J. Biol. Chem. 286(43):37793-803 (2011). (Pubmed)

◊ “pFlexAna: Detecting Conformational Changes in Remotely Related Proteins.” By A Nigham, L Tucker-Kellogg, I Mihalek, C Verma, and D Hsu*.Nucleic Acids Research, 36: W246–W251 (2008). (OxfordJournals)

◊ “De novo determination of peptide structure with solid-state magic-angle spinning NMR spectroscopy.” by Rienstra, Tucker-Kellogg, Jaroniec, Hohwy, Reif, McMahon, Tidor, Lozano-Pérez, Griffin*. Proc Natl Acad Sci U S A. 2002 Aug 6;99(16):10260-5. PDF

◊ “Engrailed (Gln50–>Lys) homeodomain-DNA complex at 1.9 A resolution: structural basis for enhanced affinity and altered specificity.” Tucker-Kellogg, Rould, Chambers, Ades, Sauer, Pabo*. Structure. 1997;5(8):1047-54. PDF

◊ “Local rule-based theory of virus shell assembly.” By Berger, Shor, Tucker-Kellogg, King*. Proc Natl Acad Sci U S A. 1994;91(16):7732-6. PDF

Heuristic Network Methods

◊ “Synergistic Target Combination Prediction From Curated Signaling Networks: Machine Learning Meets Systems Biology and Pharmacology.” By HE Chua, SS Bhowmick, L Tucker-Kellogg. Methods, in press (2017).

◊ “TINTIN: Exploiting Target Features for Signaling Network Similarity Computation and Ranking” By HE Chua, SS Bhowmick, L Tucker-Kellogg. 8th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics ACM-BCB 2017 . ACM Press, Boston, USA. (Aug 2017).

◊ “TAPESTRY: Network-centric Target Prioritization in Disease-related Signaling Networks.” By HE Chua, SS Bhowmick, Z Jie, L Tucker-Kellogg. Proceedings of 7th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB). ACM Press, Seattle, USA (2016).

◊ “TENET: Topological Feature-based Target Characterization in Signaling Networks" By Huey Eng Chua, Sourav S Bhowmick, Lisa Tucker-Kellogg, and C. Forbes Dewey, Jr. Bioinformatics 31(20): 3306-3314 (2015). (OxfordJournals) or PDF

◊ “One Feature Doesn't Fit All: Characterizing Topological Features of Targets in Signaling Networks" By Huey Eng Chua, Sourav S Bhowmick, Lisa Tucker-Kellogg Proc. 5th ACM Conference on Bioinformatics, Computational Biology and Health Informatics p.426-435 (ACM BCB 2014).

◊ "TENET: A Machine Learning-based System for Target Characterization in Signaling Networks." By HE Chua, SS Bhowmick, L Tucker-Kellogg, and CF Dewey, Jr. Proceedings of the 16th IEEE International Conference on Data Mining, IEEE ICDM (2016).

◊ “STEROID: In Silico Heuristic Target Combination Identification for Disease-Related Signaling Networks.” By Huey Eng Chua, Sourav S. Bhowmick, Lisa Tucker-Kellogg, C. Forbes Dewey, Jr. Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine – BCB2012, p.4-11 (2012). (ACM Press)

◊ “In Silico Identification of End16 Regulators in the Sea Urchin Endomesoderm Gene Regulatory Network” By H-E Chua, SS Bhowmick, L Tucker-Kellogg, Q Zhao, CF Dewey Jr, H Yu. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium.- IHI2012, p.131-140 (2012). (ACM Press)

◊ “PANI: an interactive data-driven tool for target prioritization in signaling networks.” By Chua, Huey-Eng, Sourav S. Bhowmick, Lisa Tucker-Kellogg, Qing Zhao, C. Forbes Dewey, Hanry Yu. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium (IHI'12). ACM Press. p.851-854 (2012). (ACM Press)

◊ “PANI: A Novel Algorithm for Fast Discovery of Putative Target Nodes in Signaling Networks” By HE Chua, SS Bhowmick*, CF Dewey, Jr., L Tucker-Kellogg, and H Yu. Published at the ACM Conference on Bioinformatics, Computational Biology and Biomedicine “ACM BCB” p. 284-288 (2011). (ACM Press)