Saiz Lab


Recent/Selected News

October 2021-present: Currently we have positions for graduate students, undergraduate students, and postdocs to do research in our lab.

October 2021: Our latest paper on “Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data” has been published in Scientific Reports.

October 2021: Our latest paper on “Ascertaining the initiation of epidemic resurgences: an application to the COVID-19 second surges in Europe and the Northeast United States” has been published in Royal Society Open Science.

September 2021: Check out Prof. Saiz preprint on “Multi-landmark alignment of genomic signals reveals conserved expression patterns across transcription start sites” published in bioRxiv.

September 2021: Our latest paper on “All-or-none amyloid disassembly via chaperone-triggered fibril unzipping favors clearance of α-synuclein toxic species” has been published in PNAS.

April 2021: Our latest paper on “Computational Design of Single-Stranded DNA Hairpin Aptamers Immobilized on a Biosensor Substrate” has been accepted in Scientific Reports.

March 2021: Check out Prof. Saiz preprint on “Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd” published in bioRxiv.

January 2021: Check out Prof. Saiz preprint on “Similarities and differences of the COVID-19 second surge in Europe and the Northeast United States” published in medRxiv.

January 2021: Prof. Saiz will be teaching two courses in Winter: BIM 152 (Molecular Control of Biosystems) for undergraduate students and BIM 189C (Computational tools and Applications in Bioengineering and Biomedicine) for undergraduate students.

December 2020: Check out Prof. Saiz COVID19 Web App on “COVID-19 Dynamics” at https://covid19dynamics.herokuapp.com/.

November 2020: Check out Prof. Saiz preprint on “The evolving worldwide dynamic state of the COVID-19 outbreak” published in medRxiv.

 

Research Synopsis— Modeling of Biological Networks & Systems Therapeutics Laboratory —

Computational Molecular Systems Biomedicine

The research of the Saiz Lab focuses on the integration of the molecular properties of the cellular components into the dynamics of relevant cellular processes, including signal transduction and gene regulation and their combined networks, with special interest in those altered in cancer and other diseases. Integration of the events that follow from the sensing of extracellular signals to the resulting cellular responses is needed to faithfully understand the functioning of the cell as a unit. Our work is highly interdisciplinary, drawing from techniques and tools from chemistry, physics, mathematics, computer science, biomedical sciences, and engineering; a key feature required for successful approaches to molecular systems biology. We combine computational and theoretical approaches together with experimental data to build models for accurately predicting the cellular behavior in terms of molecular properties. This type of models is also used “in reverse” to infer detailed molecular properties, such as the in vivo DNA mechanics, from physiological measurements in cell populations.In general, we want to understand and to follow the impact of molecular perturbations in the cellular components, such as a mutation in a protein or interactions with small molecules or drugs, through the different cellular processes up to the cellular behavior. [read more… Leonor Saiz profile at Biomedical Engineering]

Research Interests
Computational and theoretical approaches to the study of biological networks at the cellular and molecular level. Molecular systems biomedicine. Multiscale and multilevel approaches to biomolecular processes. Macromolecular complex assembly on DNA, membranes, and scaffolds.  Statistical mechanics basis of gene regulation and signal transduction. Noise in cellular processes. In vivo biomolecular mechanics. Molecular biophysics: membranes, membrane associated proteins, and their interactions with small molecules and drugs.

 

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