Matching Items (41)

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Data-based reconstruction of complex geospatial networks, nodal positioning and detection of hidden nodes

Description

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based solely on data? We consider the realistic situation where time series/signals can be collected from a single location. A key challenge is that the signals collected are necessarily time delayed, due to the varying physical distances from the nodes to the data collection centre. To meet this challenge, we develop a compressive-sensing-based approach enabling reconstruction of the full topology of the underlying geospatial network and more importantly, accurate estimate of the time delays. A standard triangularization algorithm can then be employed to find the physical locations of the nodes in the network. We further demonstrate successful detection of a hidden node (or a hidden source or threat), from which no signal can be obtained, through accurate detection of all its neighbouring nodes. As a geospatial network has the feature that a node tends to connect with geophysically nearby nodes, the localized region that contains the hidden node can be identified.

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Created

Date Created
  • 2016-01-06

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Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination

Description

The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies

The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies have experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence orchestrate cellular decision-making in the presence of both signal and noise. Here we tested different topologies and verified a synthetic gene circuit with mutual inhibition and auto-activations to be quadrastable, which enables direct study of quadruple cell fate determination on an engineered landscape. We show that cells indeed gravitate towards local minima and signal inductions dictate cell fates through modulating the shape of the multistable landscape. Experiments, guided by model predictions, reveal that sequential inductions generate distinct cell fates by changing landscape in sequence and hence navigating cells to different final states. This work provides a synthetic biology framework to approach cell fate determination and suggests a landscape-based explanation of fixed induction sequences for targeted differentiation.

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Created

Date Created
  • 2017-04-11

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A geometrical approach to control and controllability of nonlinear dynamical networks

Description

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to formulate a quantifiable controllability framework for nonlinear dynamical networks: a network is more controllable if the attractor network is more strongly connected. We test our control framework using examples from various models of experimental gene regulatory networks and demonstrate the beneficial role of noise in facilitating control.

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Created

Date Created
  • 2016-04-14

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Translational Regulation using Artificial Introns and ncRNAs

Description

Synthetic biology is an emerging engineering disciple, which designs and controls biological systems for creation of materials, biosensors, biocomputing, and much more. To better control and engineer these systems, modular

Synthetic biology is an emerging engineering disciple, which designs and controls biological systems for creation of materials, biosensors, biocomputing, and much more. To better control and engineer these systems, modular genetic components which allow for highly specific and high dynamic range genetic regulation are necessary. Currently the field struggles to demonstrate reliable regulators which are programmable and specific, yet also allow for a high dynamic range of control. Inspired by the characteristics of the RNA toehold switch in E. coli, this project attempts utilize artificial introns and complementary trans-acting RNAs for gene regulation in a eukaryote host, S. cerevisiae. Following modification to an artificial intron, splicing control with RNA hairpins was demonstrated. Temperature shifts led to increased protein production likely due to increased splicing due to hairpin loosening. Progress is underway to demonstrate trans-acting RNA interaction to control splicing. With continued development, we hope to provide a programmable, specific, and effective means for translational gene regulation in S. cerevisae.

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Created

Date Created
  • 2018-05

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Control of tissue homeostasis, regeneration, and degeneration by coupled bi-stable switches

Description

The Hippo signaling pathway is responsible for regulating organ size through cell proliferation, stemness, and apoptosis. Through targeting proteins Yes-associated kinase 1(YAP) and transcriptional co-activator with a PDZ-binding domain(TAZ), YAP/TAZ

The Hippo signaling pathway is responsible for regulating organ size through cell proliferation, stemness, and apoptosis. Through targeting proteins Yes-associated kinase 1(YAP) and transcriptional co-activator with a PDZ-binding domain(TAZ), YAP/TAZ are unable to enter the nucleus and bind with coactivators to express target genes. To understand YAP/TAZ dynamics and its role in tumorigenesis, tissue regeneration, and tissue degeneration, a regulatory network was modeled by ordinary differential equations. Using MATLAB, the deterministic behavior of the network was observed to determine YAP/TAZ activity in different states. Performing the bifurcation analysis of the system through Oscill8, three states were identified: tumorigenic/regenerative, degenerative, and homeostatic states. Further analysis through parameter modification allowed a better understanding of which proteins can be targeted for cancer and degenerative disease.

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Created

Date Created
  • 2020-05

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Approaches to Minimum d-Degree Arrangement

Description

Many systems in the world \u2014 such as cellular networks, the post service, or transportation pathways \u2014 can be modeled as networks or graphs. The practical applications of graph algorithms

Many systems in the world \u2014 such as cellular networks, the post service, or transportation pathways \u2014 can be modeled as networks or graphs. The practical applications of graph algorithms generally seek to achieve some goal while minimizing some cost such as money or distance. While the minimum linear arrangement (MLA) problem has been widely-studied amongst graph ordering and embedding problems, there have been no developments into versions of the problem involving degree higher than 2. An application of our problem can be seen in overlay networks in telecommunications. An overlay network is a virtual network that is built on top of another network. It is a logical network where the links between nodes represent the physical paths connecting the nodes in the underlying infrastructure. The underlying physical network may be incomplete, but as long as it is connected, we can build a complete overlay network on top of it. Since some nodes may be overloaded by traffic, we can reduce the strain on the overlay network by limiting the communication between nodes. Some edges, however, may have more importance than others so we must be careful about our selection of which nodes are allowed to communicate with each other. The balance of reducing the degree of the network while maximizing communication forms the basis of our d-degree minimum arrangement problem. In this thesis we will look at several approaches to solving the generalized d-degree minimum arrangement d-MA problem where we embed a graph onto a subgraph of a given degree. We first look into the requirements and challenges of solving the d-MA problem. We will then present a polynomial-time heuristic and compare its performance with the optimal solution derived from integer linear programming. We will show that a simple (d-1)-ary tree construction provides the optimal structure for uniform graphs with large requests sets. Finally, we will present experimental data gathered from running simulations on a variety of graphs to evaluate the efficiency of our heuristic and tree construction.

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Created

Date Created
  • 2016-05

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Engineering a Human Induced Pluripotent Stem Cell (hiPSC)-Based Model of Alzheimer's Disease

Description

Alzheimer’s Disease (AD) affects over 5 million individuals in the U.S. and has a direct cost estimated in excess of $200 billion per year. Broadly speaking, there are two forms

Alzheimer’s Disease (AD) affects over 5 million individuals in the U.S. and has a direct cost estimated in excess of $200 billion per year. Broadly speaking, there are two forms of AD—early-onset, familial AD (FAD) and late-onset-sporadic AD (SAD). Animal models of AD, which rely on the overexpression of FAD-related mutations, have provided important insights into the disease. However, these models do not display important disease-related pathologies and have been limited in their ability to model the complex genetics associated with SAD.

Advances in cellular reprogramming, have enabled the generation of in vitro disease models that can be used to dissect disease mechanisms and evaluate potential therapeutics. To that end, efforts by many groups, including the Brafman laboratory, to generated patient-specific hiPSCs have demonstrated the promise of studying AD in a simplified and accessible system. However, neurons generated from these hiPSCs have shown some, but not all, of the early molecular and cellular hallmarks associated with the disease. Additionally, phenotypes and pathological hallmarks associated with later stages of the human disease have not been observed with current hiPSC-based systems. Further, disease relevant phenotypes in neurons generated from SAD hiPSCs have been highly variable or largely absent. Finally, the reprogramming process erases phenotypes associated with cellular aging and, as a result, iPSC-derived neurons more closely resemble fetal brain rather than adult brain.

It is well-established that in vivo cells reside within a complex 3-D microenvironment that plays a significant role in regulating cell behavior. Signaling and other cellular functions, such as gene expression and differentiation potential, differ in 3-D cultures compared with 2-D substrates. Nonetheless, previous studies using AD hiPSCs have relied on 2-D neuronal culture models that do not reflect the 3-D complexity of native brain tissue, and therefore, are unable to replicate all aspects of AD pathogenesis. Further, the reprogramming process erases cellular aging phenotypes. To address these limitations, this project aimed to develop bioengineering methods for the generation of 3-D organoid-based cultures that mimic in vivo cortical tissue, and to generate an inducible gene repression system to recapitulate cellular aging hallmarks.

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Agent

Created

Date Created
  • 2018-05

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RNA-Guided Modification of Synthetic Gene Networks Using CRISPR-Cas Systems

Description

The ability to edit chromosomal regions is an important tool for the study of gene function and the ability to engineer synthetic gene networks. CRISPR-Cas systems, a bacterial RNA-guided immune

The ability to edit chromosomal regions is an important tool for the study of gene function and the ability to engineer synthetic gene networks. CRISPR-Cas systems, a bacterial RNA-guided immune system against foreign nucleic acids, have recently been engineered for a plethora of genome engineering and transcriptional regulation applications. Here we employ engineered variants of CRISPR systems in proof-of-principle experiments demonstrating the ability of CRISPR-Cas derived single-DNA-strand cutting enzymes (nickases) to direct host-cell genomic recombination. E.coli is generally regarded as a poorly recombinogenic host with double-stranded DNA breaks being highly lethal. However, CRISPR-guided nickase systems can be easily programmed to make very precise, non-lethal, incisions in genomic regions directing both single reporter gene and larger-scale recombination events deleting up to 36 genes. Genome integrated repetitive elements of variable sizes can be employed as sites for CRISPR induced recombination. We project that single-stranded based editing methodologies can be employed alongside preexisting genome engineering techniques to assist and expedite metabolic engineering and minimalized genome research.

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Agent

Created

Date Created
  • 2014-05

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A Review of Emerging Technologies and Entrepreneurship in Healthcare: Digital Health, Synthetic Biology, and Venture Capital Investment

Description

The focus shift towards Silicon Valley and similar ecosystems in the past decade, the recent boom in startups and entrepreneurship, and the resurgence of venture capital funding is fueling rapid

The focus shift towards Silicon Valley and similar ecosystems in the past decade, the recent boom in startups and entrepreneurship, and the resurgence of venture capital funding is fueling rapid advancement of modern technologies, such as software, biotechnology, and renewable energy. One facet of the growing entrepreneurial landscape features healthcare technology—a field of research centered upon various technical advances in medicine, software, and hardware. Trends in healthcare technology commercialization represent a promising opportunity for disruption in the healthcare industry. The integration of rapidly iterating software with medical research, timed perfectly with the passage of the Affordable Care Act and the boom of venture capital investment in both Big Data and mobile technology, has the healthcare technology primed for explosive growth over the next decade. Investment data indicates that strong public market activity in the past year will continue to fuel venture capital growth in both the biotechnology and digital health sectors, with the potential for multiple large exits by life sciences companies, more than even software, in the coming year.

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Created

Date Created
  • 2014-05

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Using Natural Diversity of Quorum Sensing to Expand the Synthetic Biology Toolbox

Description

Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication

Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication in which a designated sender cell produces quorum sensing molecules that modify gene expression of a designated receiver cell. While useful, these three quorum sensing pathways exhibit a nontrivial level of crosstalk, hindering robust engineering and leading to unexpected effects in a given design. To address the lack of orthogonality among these three quorum sensing pathways, previous scientists have attempted to perform directed evolution on components of the quorum sensing pathway. While a powerful tool, directed evolution is limited by the subspace that is defined by the protein. For this reason, we take an evolutionary biology approach to identify new orthogonal quorum sensing networks and test these networks for cross-talk with currently-used networks. By charting characteristics of acyl homoserine lactone (AHL) molecules used across quorum sensing pathways in nature, we have identified favorable candidate pathways likely to display orthogonality. These include Aub, Bja, Bra, Cer, Esa, Las, Lux, Rhl, Rpa, and Sin, which we have begun constructing and testing. Our synthetic circuits express GFP in response to a quorum sensing molecule, allowing quantitative measurement of orthogonality between pairs. By determining orthogonal quorum sensing pairs, we hope to identify and adapt novel quorum sensing pathways for robust use in higher-order genetic circuits.

Contributors

Created

Date Created
  • 2015-05