Matching Items (44)

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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.

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Created

Date Created
  • 2015-05

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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 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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Date Created
  • 2017-04-11

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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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Gene Networks of Fully Connected Triads With Complete Auto-Activation Enable Multistability and Stepwise Stochastic Transitions

Description

Fully-connected triads (FCTs), such as the Oct4-Sox2-Nanog triad, have been implicated as recurring transcriptional motifs embedded within the regulatory networks that specify and maintain cellular states. To explore the possible

Fully-connected triads (FCTs), such as the Oct4-Sox2-Nanog triad, have been implicated as recurring transcriptional motifs embedded within the regulatory networks that specify and maintain cellular states. To explore the possible connections between FCT topologies and cell fate determinations, we employed computational network screening to search all possible FCT topologies for multistability, a dynamic property that allows the rise of alternate regulatory states from the same transcriptional network. The search yielded a hierarchy of FCTs with various potentials for multistability, including several topologies capable of reaching eight distinct stable states. Our analyses suggested that complete auto-activation is an effective indicator for multistability, and, when gene expression noise was incorporated into the model, the networks were able to transit multiple states spontaneously. Different levels of stochasticity were found to either induce or disrupt random state transitioning with some transitions requiring layovers at one or more intermediate states. Using this framework we simulated a simplified model of induced pluripotency by including constitutive overexpression terms. The corresponding FCT showed random state transitioning from a terminal state to the pluripotent state, with the temporal distribution of this transition matching published experimental data. This work establishes a potential theoretical framework for understanding cell fate determinations by connecting conserved regulatory modules with network dynamics. Our results could also be employed experimentally, using established developmental transcription factors as seeds, to locate cell lineage specification networks by using auto-activation as a cipher.

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Date Created
  • 2014-07-24

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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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Plasmid Design for Making a HEK293t Reporter Cell Line to Study Gene Expression Dynamics

Description

Cell fate is a complex and dynamic process with many genetic components. It has often been likened to “multistable” mathematical systems because of the numerous possible “stable” states, or

Cell fate is a complex and dynamic process with many genetic components. It has often been likened to “multistable” mathematical systems because of the numerous possible “stable” states, or cell types, that cells may end up in. Due to its complexity, understanding the process of cell fate and differentiation has proven challenging. A better understanding of cell differentiation has applications in regenerative stem cell therapies, disease pathologies, and gene regulatory networks.
A variety of different genes have been associated with cell fate. For example, the Nanog/Oct-4/Sox2 network forms the core interaction of a gene network that maintains stem cell pluripotency, and Oct-4 and Sox2 also play a role in the tissue types that stem cells eventually differentiate into. Using the CRISPR/cas9 based homology independent targeted integration (HITI) method developed by Suzuki et al., we can integrate fluorescent tags behind genes with reasonable efficiency via the non-homologous end joining (NHEJ) DNA repair pathway. With human embryonic kidney (HEK) 293T cells, which can be transfected with high efficiencies, we aim to create a three-parameter reporter cell line with fluorescent tags for three different genes related to cell fate. This cell line would provide several advantages for the study of cell fate, including the ability to quantitatively measure cell state, observe expression heterogeneity among a population of genetically identical cells, and easily monitor fluctuations in expression patterns.
The project is partially complete at this time. This report discusses progress thus far, as well as the challenges faced and the future steps for completing the reporter line.

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Created

Date Created
  • 2019-05

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Mathematical Modeling of the YAP/TAZ Pathways

Description

YAP/TAZ is the key effector in the Hippo pathway, but it is also involved in many other regulatory pathways to control tissue and organ size. To better understand its regulation

YAP/TAZ is the key effector in the Hippo pathway, but it is also involved in many other regulatory pathways to control tissue and organ size. To better understand its regulation and effects in tumorigenesis and degeneration, a preliminary feedback network was created with the species YAP/TAZ, phosphorylated YAP/TAZ, LATS, miR-130a, VGLL4, and β-catenin. From this network a set of ordinary differential equations were written and analyzed for parameter effects. A model showing the healthy, tumorigenic, and degenerative states was created and preliminary parameter analysis identified the effects of parameter modifications on the overall levels of YAP/TAZ. Further analysis is required and connections with the underlying biology should continue to be pursued to better understand how parameter modifications could improve disease treatments.

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Date Created
  • 2019-05

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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