• Tucker-Kellogg lab
  • Tucker-Kellogg lab
  • Tucker-Kellogg lab
  • Tucker-Kellogg lab
  • Tucker-Kellogg lab

Publications from Lisa Tucker-Kellogg's Group

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

◊ NJM Nasir, H Heemskerk, J Jenkins, NH Hamadee, R Bunte, L Tucker-Kellogg. "Myoglobin-derived iron causes phagocyte dysfunction, wound enlargement, and impaired regeneration in pressure injuries of muscle." [BioRxiv preprint] [PDF] #PressureUlcer #GlobinIron #RedoxRegulation #Regeneration #Imaging

◊ JWK Ng, EHQ Ong, L Tucker-Kellogg (co-corresponding), G Tucker-Kellogg. “Deep learning for de-convolution of Smad2 versus Smad3 binding sites” BMC Genomics 23: 525 (2022). [Pubmed] [PDF] #Informatics #BiochemicalNetworks #ModelingMethods #Regeneration

◊ NJM Nasir, A Corrias, H Heemskerk, ET Ang, JH Jenkins, S Sebastin, L Tucker-Kellogg.“The panniculus carnosus muscle: a missing link in the chronicity of heel pressure ulcers?” Journal of the Royal Society Interface, 19(187) (2022). doi: 10.1098/rsif.2021.0631 [PDF] #PressureUlcer #Regeneration #Biophysics

◊ Lim LJ, Lim AJW, Ooi BNS, Tan JWL, Koh ET; TTSH Rheumatoid Arthritis Study Group, Chong SS, Khor CC, Tucker-Kellogg L, Lee CG, Leong KP. "Machine Learning using Genetic and Clinical Data Identifies a Signature that Robustly Predicts Methotrexate Response in Rheumatoid Arthritis." Rheumatology (Oxford). 2022 Jan 30:keac032. doi: 10.1093/rheumatology/keac032. [Pubmed] #Informatics #BiochemicalNetworks

◊ Lim AJW, Lim LJ, Ooi BNS, Koh ET, Tan JWL; TTSH RA Study Group, Chong SS, Khor CC, Tucker-Kellogg L, Leong KP, Lee CG. "Functional coding haplotypes and machine-learning feature elimination identifies predictors of Methotrexate Response in Rheumatoid Arthritis patients." EBioMedicine. 2022 Jan;75:103800. doi: 10.1016/j.ebiom.2021.103800. [Pubmed] #Informatics #BiochemicalNetworks

◊ A Surendran, CF Dewey Jr., BC Low, L Tucker-Kellogg. “A computational model of mutual antagonism in the mechano-signaling network of RhoA and Nitric Oxide” BMC Molecular and Cell Biology (2021).Oct 12; 22(Suppl 1):47. [Pubmed] [PDF] #Biophysics #RedoxRegulation #Kinetics #BiochemicalNetworks

◊ A Rouers, MHY Chng, B Lee, MP Rajapakse, K Kaur, YX Toh, D Sathiakumar, T Loy, TL Thein, VW Li, A Singhal, TW Yeo, YS Leo, K Vora, D Casimiro, Lim Bing, L Tucker-Kellogg, L Rivino, EW Newell, K Fink. “Immune cell phenotypes associated with disease severity and long-term neutralizing antibody titers after natural dengue virus infection.” Cell Reports Medicine 18;2(5):100278 (2021). [Pubmed] [PDF] #Kinetics #Informatics

◊ NS Jagannathan, CWV Hogue, L Tucker-Kellogg. “Computational modeling suggests binding-induced expansion of Epsin disordered regions upon association with AP2.” PLoS Computatonal Biology. PLoS Comput Biol. 6;17(1):e1008474. (2021). Expanded version of a prior conference paper (Pac Symp Biocomput. 25:183-194 (2020)) listed below. [Pubmed] [PDF]#Biophysics #ModelingMethods

◊ K Gupta, IC Ng, GM Balachander, BP Nguyen, L Tucker-Kellogg, BC Low, H Yu. “Bile canaliculi contract autonomously by releasing calcium into hepatocytes via mechanosensitive calcium channel.” Biomaterials. 11;259:120283 (2020). [Pubmed] [PDF] #Biophysics #Regeneration #Imaging

◊ NS Jagannathan, MO Ihsan, XX Kin, RE Welsch, MV Clément, L Tucker-Kellogg. “TRANSCOMPP: Understanding phenotypic plasticity by estimating Markov transition rates for cell state transitions.” Bioinformatics. May 1;36(9):2813-2820 (2020). [Pubmed] [PDF] #CancerPlasticity #ModelingMethods #Kinetics

◊ S Zhang, B Reljic, C Liang, B Kerouanton, JC Francisco, JH Peh, C Mary, NS Jagannathan, V Olexiouk, C Tang, G Fidelito, S Nama, RK Cheng, C Wee, LC Wang, PD Roggli, P Sampath, L Lane, E Petretto, R Sobota, S Jesuthasan, L Tucker-Kellogg, B Reversade, G Menschaert, L Sun, D Stroud, and L Ho. “Mitochondrial peptide BRAWNIN is Essential for Vertebrate Respiratory Complex III Assembly." Nature Communications, Mar 11;11(1):1312 (2020). [Pubmed] [PDF] #BiochemicalNetworks #ModelingMethods

◊ NS Jagannathan, CWV Hogue, L Tucker-Kellogg. “De novo ensemble modeling suggests that AP2-binding to disordered regions can increase steric volume of Epsin but not Eps15.” Pac Symp Biocomput. 25:183-194 (2020). [Pubmed] [PDF] #Biophysics #ModelingMethods

◊ BWS Soh, A Corrias, L Tucker-Kellogg. “Computational modeling of the thin muscle layer, panniculus carnosus, demonstrates principles of pressure injury and prophylactic dressings.” Innovations and Emerging Technologies in Wound Care, Elsevier (2020). [Chapter] [PDF] #Biophysics #PressureUlcers

◊ JL Hirpara, K Subramaniam, GL Bellot, J Qu, S Seah, T Loh, L Tucker-Kellogg, MV Clément, and S Pervaiz. “Superoxide induced inhibition of death receptor signaling is mediated via induced expression of apoptosis inhibitory protein cFLIP” Redox Biology Feb;30:101403 (2020). [Pubmed] [PDF] #RedoxRegulation #CancerPlasticity #BiochemicalNetworks

◊ C Li, KR Chng, JS Kwah, TV Av-Shalom, L Tucker-Kellogg, N Nagarajan. “An expectation-maximization algorithm enables accurate ecological modeling using longitudinal microbiome sequencing data” Microbiome 7(1):118 (2019). [Pubmed] [PDF] #Kinetics #ModelingMethods

◊ EC Saputra, L Huang, Y Chen, L Tucker-Kellogg. “Combination therapy and the evolution of resistance: the theoretical merits of synergism and antagonism in cancer.” Cancer Research 78(9): 2419-2431. (2018). [Pubmed] [PDF] #CancerPlasticity #Kinetics #NonAdditiveCombinations

◊ F Aloweni, SY Ang, S Fook-Chong, N Agus, P Yong, MM Goh, L Tucker-Kellogg, RC Soh. “A prediction tool for hospital-acquired pressure ulcers among surgical patients: Surgical pressure ulcer risk score.” International Wound Journal. 16(1): 164-175. (2018). [Pubmed] [PDF] #PressureUlcers #Informatics

◊ H Li, L Venkatraman, BC Narmada, JK White, H Yu, L Tucker-Kellogg. “Computational analysis reveals the coupling between bistability and the sign of a feedback loop in a TGF-β1 activation model.” BMC Systems Biology 11:136 (2017). [Pubmed] [PDF] #BiochemicalNetworks #NonAdditiveCombinations #Regeneration #CancerPlasticity #Kinetics

◊ J Yan, Y Yu, JW Kang, ZY Tam, S Xu, ELS Fong, SP Singh, Z Song, L Tucker-Kellogg, PTC So, H Yu. "Development of a classification model for non-alcoholic steatohepatitis (NASH) using confocal Raman micro-spectroscopy." J Biophotonics 12(10):1703-1713. (2017). [Pubmed] [PDF] #Informatics #RedoxRegulation

◊ HE Chua, SS Bhowmick, L Tucker-Kellogg. “Synergistic Target Combination Prediction From Curated Signaling Networks: Machine Learning Meets Systems Biology and Pharmacology.” Methods 129:60-80. (2017). [Pubmed] [PDF] #NonAdditiveCombination #ModelingMethods #BiochemicalNetworks

◊ 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, N Gauthier.“Membrane Tension Controls Lamellipodial Buckling and Adhesion Positioning at Leading Edge of Cells” Journal of Cell Biology 216(9): 2959-2977. (2017). [Pubmed] [PDF] #Biophysics #Kinetics #ModelingMethods

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

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

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

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

◊ HE Chua, SS Bhowmick, L Tucker-Kellogg, and CF Dewey, Jr. “TENET: A Machine Learning-based System for Target Characterization in Signaling Networks.” In the Proceedings of 16th IEEE International Conference on Data Mining, IEEE ICDM (2016). A conference-paper that describes another version of the TENET software, which we first reported in a journal (Bioinformatics 31(20):3306–3314). [IEEE] [PDF] #BiochemicalNetworks #ModelingMethods #Informatics

◊ NS Jagannathan, L Tucker-Kellogg. “Membrane Permeability During Pressure Ulcer Formation: A Computational Model of Dynamic Competition Between Cytoskeletal Damage and Repair.” Journal of Biomechanics 49(8):1311-20 (2016). [Pubmed] [PDF] #PressureUlcers #GlobinIron #RedoxRegulation #Biophysics #ModelingMethods

◊ TH Nim, L Luo, JK White, MV Clément, L Tucker-Kellogg. “Non-canonical Activation of Akt in Serum-Stimulated Fibroblasts, Revealed by Comparative Modeling of Pathway Dynamics.” PLoS Computational Biology 11(11):e1004505 (2015). [Pubmed] [PDF] #BiochemicalNetworks #Kinetics #CancerPlasticity

◊ HE Chua, SS Bhowmick, L Tucker-Kellogg, and C. Forbes Dewey, Jr. “TENET: Topological Feature-based Target Characterization in Signaling Networks" Bioinformatics 31(20): 3306-14 (2015). [Pubmed] [PDF] #BiochemicalNetworks #ModelingMethods

◊ J Ngeow, W Yu, L Yehia, F Niazi, J Chen, X Tang, B Heald, J Lei, T Romigh, L Tucker-Kellogg, KH Lim, H Song, C Eng. "Exome Sequencing Reveals Germline SMAD9 Mutation that Reduces PTEN Expression and is Associated with Hamartomatous Polyposis and Gastrointestinal Ganglioneuromas.” Gastroenterology 149(4):886-889 (2015). [Pubmed] [PDF] #BiochemicaNetworks #Informatics

◊ HE Chua, SS Bhowmick, L Tucker-Kellogg. “One Feature Doesn’t Fit All: Characterizing Topological Features of Targets in Signaling Networks.” Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB (2014). [DOI] [PDF] #BiochemicalNetworks #ModelingMethods

◊ J Wang, L Tucker-Kellogg, IC Ng, R Jia, PS Thiagarajan, JK White, H Yu. “The self-limiting dynamics of TGF-β signaling in silico and in vitro, with negative feedback through PPM1A upregulation.”  PLoS Computational Biology 10(6):e1003573 (2014). [Pubmed] [PDF] #Kinetics #BiochemicalNetworks #Regeneration #CancerPlasticity

◊ N Bahl, I Winarsih, L Tucker-Kellogg (co-corresponding), JL Ding. “Extracellular Hemoglobin Upregulates and Binds to Tissue Factor on Macrophages: Implications for Coagulation and Oxidative Stress." Thrombosis and Haemostasis 111(1):67-78 (2014). [Pubmed] [PDF] #RedoxRegulation #Regeneration #GlobinIron

◊ TH Nim, L Luo, M-V Clément, JK White, L Tucker-Kellogg. “Systematic Parameter Estimation in Data-Rich Environments for Cell Signaling Dynamics.” Bioinformatics 29(8):1044-1051 (2013). [Pubmed] [PDF] #ModelingMethods #BiochemicalNetworks #Kinetics

◊ Y Shi, G Mellier, S Huang, J White, S Pervaiz, L Tucker-Kellogg.  “Computational Modeling of LY303511 and TRAIL-Induced Apoptosis Suggests Dynamic Regulation of cFLIP.” Bioinformatics 29(3): 347-354. (2013). [Pubmed] [PDF] #CancerPlasticity #NonAdditiveCombinations #Kinetics #BiochemicalNetworks

◊ TH Nim, JK White, L Tucker-Kellogg. “SPEDRE: a Web Server for Estimating Rate Parameters of Cell Signaling Dynamics in Data-Rich Environments." Nucleic Acids Research, ePub doi: 10.1093/nar/gkt459, (2013). [Pubmed] [PDF] #ModelingMethods #BiochemicalNetworks #Kinetics

◊ L Venkatraman, L Tucker-Kellogg. "The CD47-binding Peptide of Thrombospondin-1 Induces Defenestration of Liver Sinusoidal Endothelial Cells." Liver International 33(9):1386-97 (2013). [Pubmed] [PDF] #Biophysics #Regeneration

◊ BC Narmada, S-M Chia, L Tucker-Kellogg (co-corresponding), and H Yu. “HGF regulates the activation of TGF-beta1 in rat hepatocytes and hepatic stellate cells.” J Cell Physiology, 228 (2): 393-401 (2013). [Pubmed] [PDF] #Regeneration #CancerPlasticity #BiochemicalNetworks

◊ BC Narmada, Y Kang, L Venkatraman, Q Peng, RB Sakban, BNX Jiang, RM Bunte, PTC So, L Tucker-Kellogg, HQ Mao, H Yu. “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.” Human Gene Therapy, 24(5): 508-519 (2013). [Pubmed] [PDF] #Regeneration

◊ RST Tan, B Lin, Q Liu, L Tucker-Kellogg, B Ho, BPL Leung, JL Ding. “The synergy in cytokine production through MyD88-TRIF pathways is co-ordinated with ERK phosphorylation in macrophages.” Immunology and Cell Biology 91: 377-387 (2013). [Pubmed] [PDF] #NonAdditiveCombination #Informatics #Regeneration #CancerPlasticity

◊ L Tucker-Kellogg, Y Shi, JK White, S Pervaiz. “Reactive Oxygen Species (ROS) and Sensitization to TRAIL-Induced Apoptosis, in Bayesian Network Modeling of HeLa Cell Response to LY303511.” Biochemical Pharmacology, 84 (10): 1307-17 (2012). [Pubmed] [PDF] #RedoxRegulation #ModelingMethods #BiochemicalNetworks

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

◊ K Subramaniam, JL Hirpara, L Tucker-Kellogg, G Tucker-Kellogg, S Pervaiz. “FLIP: a Flop for Execution Signals.” Cancer Letters, 332(2):151-5 (2012). [Pubmed] [PDF] #RedoxRegulation #CancerPlasticity #BiochemicalNetworks

◊ HE Chua, SS Bhowmick, L Tucker-Kellogg, Q Zhao, CF Dewey, H Yu. “PANI: an interactive data-driven tool for target prioritization in signaling networks.” Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium (IHI'12). ACM Press. p.851-854 (2012). [DOI] [PDF] #BiochemicalNetworks #ModelingMethods #Informatics

◊ HE Chua, SS Bhowmick, L Tucker-Kellogg, CF Dewey. “STEROID: In Silico Heuristic Target Combination Identification for Disease-Related Signaling Networks.” Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine – BCB2012, p.4-11 (2012). [DOI] [PDF] #NonAdditiveCombinations #ModelingMethods #BiochemicalNetworks

◊ L Venkatraman, S Chia, BC Narmada, LS Poh, H Li, R Sakban, RR Jia, S Shen, JK White, SS Bhowmick, CF Dewey, PT So, L Tucker-Kellogg (co-corresponding), H Yu. “Plasmin Triggers a Switch-like Decrease in Thrombospondin-Dependent Activation of TGF-beta1” Biophysical Journal, 103: 1060–1068 (2012). [Pubmed] [PDF] #NonAdditiveCombinations #Kinetics #Regeneration #BiochemicalNetworks #CancerPlasticity

◊ L Huang, CQ Pan, B Li, L Tucker-Kellogg, B Tidor, YZ Chen, BC Low. "Simulating EGFR-ERK Signaling Control by Scaffold Proteins KSR and MP1 Reveal Differential Ligand-Sensitivity co-regulated by Cbl-CIN85 and Endophilin" PLoS One. 6(8):e22933 (2011). [Pubmed] [PDF] #CancerPlasticity #BiochemicalNetworks #Kinetics

◊ L Venkatraman, H Li, CF Dewey Jr, JK White, SS Bhowmick, H Yu, L Tucker-Kellogg. “The Steady States and Dynamics of Urokinase-mediated Plasmin Activation, in Silico and in Vitro” Biophysical Journal 101:1825–1834 (2011). [Pubmed] [PDF] #Kinetics #BiochemicalNetworks #Regeneration #CancerPlasticity

◊ A Ananthanarayanan, L Tucker-Kellogg, BC Narmada, L Venkatraman, NA Abdul Rahim, Y Wang, CH Kang, H Yu. Systems Biology in Biomaterials and Tissue Engineering.” Comprehensive Biomaterials, Vol. 5, p.177-188 (2011).[PDF] #Regeneration

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

◊ HE Chua, SS Bhowmick, CF Dewey, Jr., L Tucker-Kellogg, and H Yu. “PANI: A Novel Algorithm for Fast Discovery of Putative Target Nodes in Signaling Networks” Published at the ACM Conference on Bioinformatics, Computational Biology and Biomedicine “ACM BCB” (2011). [DOI] [PDF] #BiochemicalNetworks #ModelingMethods

◊ N Bahl, R Du, I Winarsih, B Ho, L Tucker-Kellogg, B Tidor, and JL Ding. “Delineation of Lipopolysaccharide (LPS)-binding Sites on Hemoglobin: From in silico predictions to biophysical characterization.” Journal of Biological Chemistry 286(43):37793-803 (2011). [Pubmed] [PDF] #RedoxRegulation #Biophysics #GlobinIron

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

◊ W-X Zhang, L Tucker-Kellogg, BC Narmada, L Venkatraman, S Chang, Y Lu, H Yu. “Cell-Delivery Therapeutics for Liver Regeneration” Advanced Drug Delivery Reviews 62(7-8):814-26 (2010). [Pubmed] [PDF]#Regeneration

◊ Y Shi, SM Varghese, S Huang, J White, S Pervaiz, L Tucker-Kellogg. “Computational Modeling of Pathway Dynamics For Detecting Drug Effects: Paradoxical Effects of LY303511 on TRAIL-Induced Apoptosis.” Computational Systems Bioinformatics (CSB09), 8: 213-224 (2009). [PDF] #Kinetics #BiochemicalNetworks #RedoxRegulation #NonAdditiveCombinations

◊ A Nigham, L Tucker-Kellogg, I Mihalek, C Verma, and D Hsu. “pFlexAna: Detecting Conformational Changes in Remotely Related Proteins.” Nucleic Acids Research, 36: W246–W251 (2008). [Pubmed] [PDF] #Biophysics #ModelingMethods

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

◊ CM Rienstra, L Tucker-Kellogg, CP Jaroniec, M Hohwy , B Reif, MT McMahon, B Tidor, T Lozano-Pérez, RG Griffin. "De novo determination of peptide structure with solid-state magic-angle spinning NMR spectroscopy." Proc. Natl. Acad. Sci. USA, Aug 6: 99(16): 10260-5 (2002). [Pubmed] [PDF] #Biophysics #ModelingMethods

◊ L Tucker-Kellogg, M Rould, C Chambers, S Ades, RT Sauer, and CO Pabo. "Engrailed Gln50 - Lys homeodomain-DNA complex at 1.9 Å resolution: structural basis for enhanced affinity and altered specificity" Structure, Vol. 5, No. 8, pp. 1047-1054 (1997). [Pubmed] [PDF] #Biophysics #ModelingMethods

◊ B Berger, P Shor, L Tucker-Kellogg, J King. "Local rule-based theory of virus shell assembly" Proc. Natl. Acad. Sci. USA, Vol. 91, pp.7732-7736 (1994). [Pubmed] [PDF] #Biophysics #ModelingMethods

ORCID iD iconorcid.org/0000-0002-1301-7069