Shirley Pepke

ORCID: 0000-0003-3516-7209
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About
Contact & Profiles
Research Areas
  • Bioinformatics and Genomic Networks
  • Computational Drug Discovery Methods
  • Gene expression and cancer classification
  • Genomics and Chromatin Dynamics
  • Genetics, Bioinformatics, and Biomedical Research
  • RNA Research and Splicing
  • RNA modifications and cancer
  • Cancer-related molecular mechanisms research
  • RNA and protein synthesis mechanisms
  • Biomedical Text Mining and Ontologies
  • Neuroscience and Neuropharmacology Research
  • Molecular Sensors and Ion Detection
  • MicroRNA in disease regulation
  • Protein Structure and Dynamics
  • Artificial Intelligence in Games
  • Distributed and Parallel Computing Systems
  • Chromosomal and Genetic Variations
  • Single-cell and spatial transcriptomics
  • Axial and Atropisomeric Chirality Synthesis
  • Photoreceptor and optogenetics research
  • DNA and Nucleic Acid Chemistry
  • Advanced Data Processing Techniques
  • Advanced biosensing and bioanalysis techniques
  • Fault Detection and Control Systems
  • Genomics and Phylogenetic Studies

California Institute of Technology
2009-2015

Caelum Research Corporation (United States)
2007

During the acquisition of memories, influx Ca2+ into postsynaptic spine through pores activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change strength excitatory synapses. The pattern Ca2+influx during first few seconds activity is interpreted within Ca2+-dependent signaling network such synaptic eventually either potentiated or depressed. Many critical enzymes control plasticity,including Ca2+/calmodulin-dependent protein kinase II (CaMKII), are regulated by...

10.1371/journal.pcbi.1000675 article EN cc-by PLoS Computational Biology 2010-02-11

Cis -regulatory modules (CRMs) function by binding sequence specific transcription factors, but the relationship between in vivo physical and regulatory capacity of factor-bound DNA elements remains uncertain. We investigate this for well-studied Twist factor Drosophila melanogaster embryos analyzing genome-wide occupancy testing functional significance occupied regions motifs within regions. ChIP-seq data efficiently identified previously studied Twist-dependent CRMs robustly predicted new...

10.1101/gr.104018.109 article EN cc-by-nc Genome Research 2011-03-07

We tested whether self-organizing maps (SOMs) could be used to effectively integrate, visualize, and mine diverse genomics data types, including complex chromatin signatures. A fine-grained SOM was trained on 72 ChIP-seq histone modifications DNase-seq sets from six biologically cell lines studied by The ENCODE Project Consortium. mined the resulting identify signatures related sequence-specific transcription factor occupancy, sequence motif enrichment, biological functions. To highlight...

10.1101/gr.158261.113 article EN cc-by-nc Genome Research 2013-10-29

De novo inference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into few subtypes or rely upon analysis pairwise correlations that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power discern targetable pathways, but this is commonly thought an intractable computational problem. In work we adapt recently developed...

10.1186/s12920-017-0245-6 article EN cc-by BMC Medical Genomics 2017-03-09

Abstract Background De novo inference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into few subtypes or rely upon analysis pairwise correlations (co-expression) that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power discern targetable pathways, but this is commonly thought an intractable computational problem....

10.1101/043257 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2016-03-11

Event Abstract Back to Modelling calcium-dependent proteins in the spine - challenges and solutions Melanie I. Stefan1*, Shirley Pepke1, Stefan Mihalas1, Thomas Bartol2, Terrence Sejnowki2 Mary B. Kennedy1 1 California Institute of Technology, Biology Division, United States 2 Salk Institute, Synaptic plasticity is mediated by calcium signalling postsynaptic spine. One hypothesis suggests that direction determined relative activation two Ca2+-/calmodulin dependent proteins, CaMKII...

10.3389/conf.fninf.2014.08.00091 article EN cc-by Frontiers in Neuroinformatics 2014-01-01

Event Abstract Back to Multi-Stage Modeling of the Kinetics Activation CaMKII Melanie Stefan1*, Shirley Pepke1, Stefan Mihalas1, Thomas Bartol2, Terrence Sejnowski2 and Mary Kennedy1 1 California Institute Technology, Div. Biology, United States 2 Salk Institute, Ca 2+ /calmodulin-dependent protein kinase (CaMKII) plays an important role in induction long-term potentiation formation memory. It is abundant dendritic spines, activated when flows into postsynaptic cytosol through open NMDA-type...

10.3389/conf.fninf.2011.08.00033 article EN cc-by Frontiers in Neuroinformatics 2011-01-01

Background / Purpose: Modelling post-synaptic proteins poses three technical problems: small absolute molecule numbers, large numbers of possible states, and the complex geometry spine, which is not a well-mixed compartment. Computational approaches are needed that solve all these problems. Main conclusion: Stochastic simulation methods can be used for systems with agent-based to represent multi-state molecules, spatial simulate events in geometries. We stochastic simulator MCell...

10.7490/f1000research.1092544.1 article EN F1000Research 2012-10-19

Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility in analyzing differential of groups genes tumor RNA-seq a way that may be helpful advancing precision oncology. However, produces many factors can challenging to analyze and connect existing understanding. To facilitate such connections, we have built website, CorExplorer, allows users interactively explore the data answer common questions...

10.3791/60431 article EN Journal of Visualized Experiments 2019-10-11

Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility in analyzing differential of groups genes tumor RNA-seq a way that may be helpful advancing precision oncology. However, produces many factors can challenging to analyze and connect existing understanding. To facilitate such connections, we have built website, CorExplorer, allows users interactively explore the data answer common questions...

10.3791/60431-v article EN Journal of Visualized Experiments 2019-10-11
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