DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

A Stationless Bikeshare Proof of Concept for College Campuses

Bikeshares promote healthy lifestyles and sustainability among commuters, casual riders, and tourists. However, the central pillar of modern systems, the bike station, cannot be easily integrated into a compact college campus. Fixed stations lack the flexibility to meet the needs of college students who make quick, short-distance trips. Additionally, the necessary cost of implementing and maintaining each station prohibits increasing the number of stations for user convenience. Therefore, the team developed a stationless bikeshare based on a smartlock permanently attached to bicycles in the system. The smartlock system design incorporates several innovative approaches to provide usability, security, and reliability that overcome the limitations of a station centered design. A focus group discussion allowed the team to receive feedback on the early lock, system, and website designs, identify improvements and craft a pleasant user experience. The team designed a unique, two-step lock system that is intuitive to operate while mitigating user error. To ensure security, user access is limited through near field ii communications (NFC) technology connected to a mechatronic release system. The said system relied on a NFC module and a servo working through an Arduino microcontroller coded in the Arduino IDE. To track rentals and maintain the system, each bike is fitted with an XBee module to communicate with a scalable ZigBee mesh network. The network allows for bidirectional, real-time communication with a Meteor.js web application, which enables user and administrator functions through an intuitive user interface available on mobile and desktop. The development of an independent smartlock to replace bike stations is essential to meet the needs of the modern college student. With the goal of creating a bikeshare that better serves college students, Team BIKES has laid the framework for a system that is affordable, easily adaptable, and implementable on any university expressing an interest in bringing a bikeshare to its campus.

GABRIEL URBAIN FAURÉ, THE UNSUNG MODERNIST: A PERFORMANCE SURVEY OF SELECTED LATE WORKS WRITTEN AFTER 1892 FOR PIANO SOLO, AND PIANO IN COLLABORATION WITH VIOLIN, VIOLONCELLO, AND VOICE

Gabriel Urbain Fauré lived during one of the most exciting times in music history. Spanning a life of 79 years (1845-1924), he lived through the height of Romanticism and the experimental avant-garde techniques of the early 20th century. In Fauré's music, one can find traces of Chopin, Liszt, Mendelssohn, Debussy and Poulenc. One can even argue that Fauré presages Skryabin and Shostakovich. The late works of Gabriel Fauré, chiefly those composed after 1892, testify to the argument that Fauré holds an important position in the shift from tonal to atonal composition and should be counted among such transitional composers as Gustav Mahler, Claude Debussy, Erik Satie, Richard Strauss, and Ferruccio Busoni. Fauré's unique way of fashioning harmonic impetus of almost purely linear means, resulting in a synthesis of harmonic and melodic devices, led me to craft the term mélodoharmonique. This term refers to a contrapuntally motivated technique of composition, particularly in a secondary layer of musical texture, in which a component of harmonic progression (i.e. arpeggiation, broken chord, etc.) is fused with linear motivic or thematic development. This dissertation seeks to bring to public attention through exploration in lecture and recital format, certain works of Gabriel Fauré, written after 1892. The repertoire will be selected from works for solo piano and piano in collaboration with violin, violoncello, and voice, which support the notion of Fauré as a modernist deserving larger recognition for his influence in the transition to atonal music. The recital repertoire includes the following--Song Cycles: La bonne chanson, opus 61; La chanson d'Ève, opus 95; Le jardin clos, opus 106; Mirages, opus 113; L'horizon chimérique, opus 118; Piano Works: Prelude in G minor opus 103, No. 3; Prelude in E minor opus 103, No. 9; Eleventh Nocturne, opus 104, No.1; Thirteenth Nocturne, opus 119; Chamber Works: Second Violin Sonata, opus 108; First Violoncello Sonata, opus 109; Second Violoncello Sonata, opus 117.