M
Melody Morris
Researcher at Novartis
Publications - 32
Citations - 1567
Melody Morris is an academic researcher from Novartis. The author has contributed to research in topics: Fuzzy logic & Centenarian. The author has an hindex of 13, co-authored 28 publications receiving 1295 citations. Previous affiliations of Melody Morris include Massachusetts Institute of Technology & Merck & Co..
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Journal ArticleDOI
TORC1 inhibition enhances immune function and reduces infections in the elderly.
Joan Mannick,Melody Morris,Hans-Ulrich P. Hockey,Guglielmo Roma,Martin Beibel,Kenneth Kulmatycki,Mollie Watkins,Tea Shavlakadze,Weihua Zhou,Dean Quinn,David J. Glass,Lloyd B. Klickstein +11 more
TL;DR: It is shown that low-dose TORC1 inhibitor therapy in elderly humans decreased the incidence of all infections, improved influenza vaccination responses, and up-regulated antiviral immunity, as well as an up-regulation of antiviral gene expression and an improvement in the response to influenza vaccination in this treatment group.
Journal ArticleDOI
Logic-Based Models for the Analysis of Cell Signaling Networks
Melody Morris,Julio Saez-Rodriguez,Julio Saez-Rodriguez,Peter K. Sorger,Peter K. Sorger,Douglas A. Lauffenburger +5 more
TL;DR: In this article, a review of recent advances in applying logic-based modeling to mammalian cell biology can be found, along with case studies that demonstrate the utility of such models for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks.
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CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms
Camille Terfve,Thomas Cokelaer,David Henriques,Aidan MacNamara,Emanuel Gonçalves,Melody Morris,Martijn P. van Iersel,Douglas A. Lauffenburger,Julio Saez-Rodriguez +8 more
TL;DR: In this article, the authors propose a formalism that can take advantage of complex and dynamic networks to build models of cellular signaling in both physiological and diseased situations, using context-specific medium/high throughput proteomic data.
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Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli.
Melody Morris,Julio Saez-Rodriguez,Julio Saez-Rodriguez,David C. Clarke,Peter K. Sorger,Peter K. Sorger,Douglas A. Lauffenburger +6 more
TL;DR: This work converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways, and generates a Computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone.
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Comparing Signaling Networks between Normal and Transformed Hepatocytes Using Discrete Logical Models
Julio Saez-Rodriguez,Leonidas G. Alexopoulos,Mingsheng Zhang,Melody Morris,Douglas A. Lauffenburger,Peter K. Sorger +5 more
TL;DR: In this paper, the authors combine network analysis and functional experimentation by using a hybrid approach in which graphs are converted into simple mathematical models that can be trained against biochemical data, which can be used to predict the responses of cell signaling proteins to specific ligands or drugs.