Genomic Regulatory Networks, Reduction Mappings and Control

All high-level living organisms are made of small cell units, containing DNA, RNA, genes, proteins etc. Genes are important components of the cells and it is necessary to understand the inter-gene relations, in order to comprehend, predict and ultimately intervene in the cells’ dynamics. Genetic regulatory networks (GRN) represent the gene interactions that dictate the cell behavior. Translational genomics aims to mathematically model GRNs and one of the main goals is to alter the networks’ behavior away from undesirable phenotypes such as cancer. The mathematical framework that has been often used for modeling GRNs is the probabilistic Boolean network (PBN), which is a collection of constituent Boolean networks with perturbation, BNp. This dissertation uses BNps, to model gene regulatory networks with an intent of designing stationary control policies (CP) for the networks to shift their dynamics toward more desirable states. Markov Chains (MC) are used to represent the PBNs and stochastic control has been employed to find stationary control policies to affect steady-state distribution of the MC. However, as the number of genes increases, it becomes computationally burdensome, or even infeasible, to derive optimal or greedy intervention policies. This dissertation considers the problem of modeling and intervening in large GRNs. To overcome the computational challenges associated with large networks, two approaches are proposed: first, a reduction mapping that deletes genes from the network; and second, a greedy control policy that can be directly designed on large networks. Simulation results show that these methods achieve the goal of controlling large networks by shifting the steady-state distribution of the networks toward more desirable states. Furthermore, a new inference method is used to derive a large 17-gene Boolean network from microarray experiments on gastrointestinal cancer samples. The new algorithm has similarities to a previously developed well-known inference method, which uses seed genes to grow subnetworks, out of a large network; however, it has major differences with that algorithm. Most importantly, the objective of the new algorithm is to infer a network from a seed gene with an intention to derive the Gene Activity Profile toward more desirable phenotypes. The newly introduced reduction mappings approach is used to delete genes from the 17-gene GRN and when the network is small enough, an intervention policy is designed for the reduced network and induced back to the original network. In another experiment, the greedy control policy approach is used to directly design an intervention policy on the large 17-gene network to beneficially change the long-run behavior of the network. Finally, a novel algorithm is developed for selecting only non-isomorphic BNs, while generating synthetic networks, using a method that generates synthetic BNs, with a prescribed set of attractors. The goal of the new method described in this dissertation is to discard isomorphic networks

Stochastic analysis of nonlinear dynamics and feedback control for gene regulatory networks with applications to synthetic biology

The focus of the thesis is the investigation of the generalized repressilator model (repressing genes ordered in a ring structure). Using nonlinear bifurcation analysis stable and quasi-stable periodic orbits in this genetic network are characterized and a design for a switchable and controllable genetic oscillator is proposed. The oscillator operates around a quasi-stable periodic orbit using the classical engineering idea of read-out based control. Previous genetic oscillators have been designed around stable periodic orbits, however we explore the possibility of quasi-stable periodic orbit expecting better controllability. The ring topology of the generalized repressilator model has spatio-temporal symmetries that can be understood as propagating perturbations in discrete lattices. Network topology is a universal cross-discipline transferable concept and based on it analytical conditions for the emergence of stable and quasi-stable periodic orbits are derived. Also the length and distribution of quasi-stable oscillations are obtained. The findings suggest that long-lived transient dynamics due to feedback loops can dominate gene network dynamics. Taking the stochastic nature of gene expression into account a master equation for the generalized repressilator is derived. The stochasticity is shown to influence the onset of bifurcations and quality of oscillations. Internal noise is shown to have an overall stabilizing effect on the oscillating transients emerging from the quasi-stable periodic orbits. The insights from the read-out based control scheme for the genetic oscillator lead us to the idea to implement an algorithmic controller, which would direct any genetic circuit to a desired state. The algorithm operates model-free, i.e. in principle it is applicable to any genetic network and the input information is a data matrix of measured time series from the network dynamics. The application areas for readout-based control in genetic networks range from classical tissue engineering to stem cells specification, whenever a quantitatively and temporarily targeted intervention is required

Applying the Free-Energy Principle to Complex Adaptive Systems

The free energy principle is a mathematical theory of the behaviour of self-organising systems that originally gained prominence as a unified model of the brain. Since then, the theory has been applied to a plethora of biological phenomena, extending from single-celled and multicellular organisms through to niche construction and human culture, and even the emergence of life itself. The free energy principle tells us that perception and action operate synergistically to minimize an organism’s exposure to surprising biological states, which are more likely to lead to decay. A key corollary of this hypothesis is active inference—the idea that all behavior involves the selective sampling of sensory data so that we experience what we expect to (in order to avoid surprises). Simply put, we act upon the world to fulfill our expectations. It is now widely recognized that the implications of the free energy principle for our understanding of the human mind and behavior are far-reaching and profound. To date, however, its capacity to extend beyond our brain—to more generally explain living and other complex adaptive systems—has only just begun to be explored. The aim of this collection is to showcase the breadth of the free energy principle as a unified theory of complex adaptive systems—conscious, social, living, or not

Análisis de relaciones fenotípicas mediante el uso de ontologías biomédicas: aplicaciones a enfermedades genéticas

A partir de la definición de los perfiles fenotípicos de cada gen y la construcción de una red de relaciones fenotípicas entre genes para estudiar las implicaciones funcionales de aquellos genes fenotípicamente similares. Esta red contiene nuevas relaciones entre genes causantes de la enfermedad, las cuales fueron útiles para explorar las bases moleculares de los procesos patológicos. Posteriormente, se desarrolló una herramienta (PhenUMA, www.phenuma.uma.es) que permite la consulta de genes y enfermedades para obtener sus relaciones fenotípicas y funcionales. Además, se hizo uso de herramientas de minería de textos para extraer de la bibliografía relaciones entre estos genes y enfermedades. El objetivo es incluir en PhenUMA relaciones procedentes de la bibliografía no presentes en las bases de datos públicas. Por último, se analizaron las relaciones genotipo-fenotipo en un conjunto heterogéneo de pacientes con síndromes genómicos procedente de DECIPHER. Se estudió la sintomatología común a los pacientes cuyas regiones afectadas son solapantes, para identificar regiones potencialmente patológicas. Esta información se usó para construir una red de pacientes. El análisis de esta red permitió identificar relaciones significativas entre características clínicas y variaciones estructurales. Además, se detectaron potenciales nuevos síndromes.El incremento en la eficiencia de las técnicas de alto rendimiento y el avance de los métodos de integración y análisis de información, han permitido estudiar las enfermedades integrando varios niveles de complejidad. El estudio de toda esta información ha proporcionado otra visión de enfermedades complejas y multifactoriales como el cáncer, la obesidad o la diabetes. El caso de las enfermedades raras es especialmente complejo debido a la heterogeneidad de las etiologías y la baja disponibilidad de muestras de pacientes y familias para el análisis molecular y fenotípico de estas patologías. La integración de datos masivos generados a partir de técnicas experimentales de alto rendimiento facilita el estudio de las enfermedades genéticas o de baja prevalencia. Trabajos como el desarrollado por Goh et al., 2007 resalta la importancia de estudiar la complejidad de las relaciones entre los genes asociados a enfermedades. Este estudio muestra que las enfermedades generalmente manifiestan diversos síntomas y que distintas patologías se pueden asociar a fenotipos patológicos similares; asociados a alteraciones en procesos biológicos relacionados funcionalmente. Si bien uno de los grandes problemas de la integración de información (pato)fenotípica radica en lo sujeta que está al lenguaje natural, herramientas como HPO facilitan esta integración. Para profundizar en las relaciones fenotípicas entre enfermedades, en esta tesis se trabaja en la hipótesis de que: El estudio de las enfermedades complejas a partir del perfil fenotípico que las describe y la integración de esta información en su contexto biomolecular permite identificar los mecanismos moleculares afectados en múltiples procesos patológicos. Para ello en primer lugar se analizaron las relaciones fenotípicas entre genes

2021 Student Symposium Research and Creative Activity Book of Abstracts

The UMaine Student Symposium (UMSS) is an annual event that celebrates undergraduate and graduate student research and creative work. Students from a variety of disciplines present their achievements with video presentations. It’s the ideal occasion for the community to see how UMaine students’ work impacts locally – and beyond. The 2021 Student Symposium Research and Creative Activity Book of Abstracts includes a complete list of student presenters as well as abstracts related to their works

Macroevolution: Explanation, Interpretation and Evidence

info:eu-repo/semantics/publishedVersio

Audit of Antenatal Testing of Sexually Transmissible Infections and Blood Borne Viruses at Western Australian Hospitals

In August 2007, the Western Australian Department of Health (DOH) released updated recommendations for testing of sexually transmissible infections (STI) and blood-borne viruses (BBV) in antenates. Prior to this, the Royal Australian & New Zealand College of Obstetricians & Gynaecologists (RANZCOG) antenatal testing recommendations had been accepted practice in most antenatal settings. The RANZCOG recommends that testing for HIV, syphilis, hepatitis B and C be offered at the first antenatal visit. The DOH recommends that in addition, chlamydia testing be offered. We conducted a baseline audit of antenatal STI/BBV testing in women who delivered at selected public hospitals before the DOH recommendations. We examined the medical records of 200 women who had delivered before 1st July 2007 from each of the sevenWAhospitals included in the audit. STI and BBV testing information and demographic data were collected. Of the 1,409 women included, 1,205 (86%) were non-Aboriginal and 200 (14%) were Aboriginal. High proportions of women had been tested for HIV (76%), syphilis (86%), hepatitis C (87%) and hepatitis B (88%). Overall, 72% of women had undergone STI/BBV testing in accordance with RANZCOG recommendations. However, chlamydia testing was evident in only 18% of records. STI/BBV prevalence ranged from 3.9% (CI 1.5– 6.3%) for chlamydia, to 1.7% (CI 1–2.4%) for hepatitis C, 0.7% (CI 0.3–1.2) for hepatitis B and 0.6% (CI 0.2–1) for syphilis. Prior to the DOH recommendations, nearly three-quarters of antenates had undergone STI/BBV testing in accordance with RANZCOG recommendations, but less than one fifth had been tested for chlamydia. The DOH recommendations will be further promoted with the assistance of hospitals and other stakeholders. A future audit will be conducted to determine the proportion of women tested according to the DOH recommendations. The hand book from this conference is available for download Published in 2008 by the Australasian Society for HIV Medicine Inc © Australasian Society for HIV Medicine Inc 2008 ISBN: 978-1-920773-59-

PSA 2018

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018