Ludmila V. Danilova

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Modeling of signal driven transcriptional reprogramming is critical for understanding of organism development, human disease, and cell biology. Many current modeling techniques discount key features of the biological sub-systems when modeling multiscale, organism-level processes. We present a mechanistic hybrid model, GESSA, which integrates a novel pooled(More)
  • John Wrangle, Emi Ota Machida, +16 authors Malcolm V Brock
  • 2014
PURPOSE Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality in the world. Novel diagnostic biomarkers may augment both existing NSCLC screening methods as well as molecular diagnostic tests of surgical specimens to more accurately stratify and stage candidates for adjuvant chemotherapy. Hypermethylation of CpG islands is a common and(More)
Tumor-infiltrating immune cells have been linked to prognosis and response to immunotherapy; however, the levels of distinct immune cell subsets and the signals that draw them into a tumor, such as the expression of antigen presenting machinery genes, remain poorly characterized. Here, we employ a gene expression-based computational method to profile the(More)
The RNAKinetics server (http://www.ig-msk.ru/RNA/kinetics) is a web interface for the newly developed RNAKinetics software. The software models the dynamics of RNA secondary structure by the means of kinetic analysis of folding transitions of a growing RNA molecule. The result of the modeling is a kinetic ensemble, i.e. a collection of RNA structures that(More)
It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data(More)
PURPOSE Genome-wide DNA methylation analyses have identified hundreds of candidate DNA-hypermethylated genes in cancer. Comprehensive functional analyses provide an understanding of the biologic significance of this vast amount of DNA methylation data that may allow the determination of key epigenetic events associated with tumorigenesis. EXPERIMENTAL(More)
Development of head and neck squamous cell carcinoma (HNSCC) is characterized by accumulation of mutations in several oncogenes and tumor suppressor genes. We have formerly described the mutation pattern of HNSCC and described NOTCH signaling pathway alterations. Given the complexity of the HNSCC, here we extend the previous study to understand the overall(More)
Head and neck squamous cell carcinoma (HNSCC) is largely divided into two groups based on their etiology, human papillomavirus (HPV)-positive and -negative. Global DNA methylation changes are known to drive oncogene and tumor suppressor expression in primary HNSCC of both types. However, significant heterogeneity in DNA methylation within the groups results(More)
Cellular function and diversity are orchestrated by complex interactions of fundamental biomolecules including DNA, RNA and proteins. Technological advances in genomics, epigenomics, transcriptomics and proteomics have enabled massively parallel and unbiased measurements. Such high-throughput technologies have been extensively used to carry out broad,(More)
MELANOMA BRIDGE 2015 KEYNOTE SPEAKER PRESENTATIONS Molecular and immuno-advances K1 Immunologic and metabolic consequences of PI3K/AKT/mTOR activation in melanoma Vashisht G. Y. Nanda, Weiyi Peng, Patrick Hwu, Michael A. Davies K2 Non-mutational adaptive changes in melanoma cells exposed to BRAF and MEK inhibitors help the establishment of drug resistance(More)