Dr. Lisa Tucker-Kellogg

Lee Kuan Yew Postdoctoral Fellow
Faculty Member of the Singapore-MIT Alliance
Department of Computer Science
National University of Singapore
Singapore 117590

Office: NUS Room #COM1-03-24
Phone: (+65) 6516-2865
Departmental Fax: (+65) 6779-4580
Personal Fax: 1-419-502-0572
Email: tucker [at] comp [dot] "nus.edu.sg"

HELP WANTED!

Now Hiring: Laboratory Technician / Research Assistant

Undergrad research (HYP/UROP) project available also.

Research Interests

COMPUTATIONAL SYSTEMS BIOLOGY

• Decomposition, Discretization, and Probabilistic Graphical Models as tools for approaching the problem of Parameter Estimation. Relevant work: “Composing Globally Consistent Pathway Parameter Estimates through Belief Propagation.” Workshop on Algorithms for BioInformatics (2007) 420-430.
  
  
• The role of LY29 and LY30 in ROS production. Inspired by the paper: “LY294002 and LY303511 sensitize tumor cells to drug-induced apoptosis via intracellular hydrogen peroxide production independent of the phosphoinositide 3-kinase-Akt pathway.” Cancer Research 2005 65:6264.
  
  
• The role of Superoxide in cell survival signaling. Drugs that promote accumulation of superoxide also promote activation of Akt, a kinase that promotes survival. We hypothesize reactions that are involved, model their dynamics, and seek to design more focused experiments that can help confirm the original hypotheses. Inspired by the paper: “Phosphorylation of the survival kinase Akt by superoxide…” by Lim and Clement in Free Radic Biol Med 42:1178.
  
  
• The role of LY30 in TRAIL signaling. The drug LY303511 causes cancer cells to become increasingly susceptible to death signaling such as by TRAIL (TNF-related apoptosis inducing ligand). We model the upstream events in TRAIL signaling, such as the oligomerization of death receptors, formation of the DISC (death inducing signaling complex), and inhibition by cFLIP. Our eventual goal is to predict different TRAIL responses. Inspired by the paper: “LY303511 amplifies TRAIL-induced apoptosis in tumor cells…” by Poh, Huang, Hirpara and Pervaiz.
  
  
• Machine learning to categorize LSC images of cell death. This is a potential project, not yet claimed, for somebody with a machine learning background and a willingness to learn the domain area, to analyze the LSC images already being produced by the above LY30 projects, with the aim of (1) automatially categorizing the type of cell death, and (2) finding "fingerprints" that would allow the same categorization to occur without requiring as much data collection, such as with less time or with less sophisticated equipment.

COMPUTATIONAL STRUCTURAL BIOLOGY (Previously my main focus)

• Automated analysis of flexibility in protein structures. ONGOING WORK: Algorithmic development of pFlexAna and adapting the ideas of pFlexAna to additional problems such as visualization of molecular dynamics trajectories. See “pFlexAna: Detecting Conformational Changes in Remotely Related Proteins.” By Nigham, Tucker-Kellogg, Mihalek, Verma, and Hsu. Nucleic Acids Research, in press 2008.
  
  
• Systematic Conformational Search. ONGOING WORK: Studying more difficult cases with the same method and adapting the method for new applications. See "De novo determination of peptide structure with solid-state magic-angle spinning NMR spectroscopy." By by Rienstra, Tucker-Kellogg, Jaroniec, Hohwy, Tidor, Lozano-Pérez, Griffin. PROC. NATL. ACAD. SCI. USA, 2002 Aug 6: 99(16): 10260-5. (cited 83 times)
  
  
• [Completed] X-ray crystallography towards better understanding protein-DNA binding. "Engrailed Gln50 - Lys homeodomain-DNA complex at 1.9 A resolution: structural basis for enhanced affinity and altered specificity" by Tucker-Kellogg, Rould, Chambers, Ades, Sauer, and Pabo. STRUCTURE, Vol. 5, No. 8, pp. 1047-1054, 1997. PMID: 9309220 (cited 59 times)
  
  
• [Completed] Virus shell assembly. "Local rule-based theory of virus shell assembly" by Berger, Shor, Tucker-Kellogg, King. PROC. NATL. ACAD. SCI. USA Vol. 91, pp.7732-7736, 1994. PMID: 8052652 (cited 73 times)