High-Throughput SNP Genotyping by SBE/SBH

Despite much progress over the past decade, current Single Nucleotide Polymorphism (SNP) genotyping technologies still offer an insufficient degree of multiplexing when required to handle user-selected sets of SNPs. In this paper we propose a new genotyping assay architecture combining multiplexed solution-phase single-base extension (SBE) reactions with sequencing by hybridization (SBH) using universal DNA arrays such as all $k$-mer arrays. In addition to PCR amplification of genomic DNA, SNP genotyping using SBE/SBH assays involves the following steps: (1) Synthesizing primers complementing the genomic sequence immediately preceding SNPs of interest; (2) Hybridizing these primers with the genomic DNA; (3) Extending each primer by a single base using polymerase enzyme and dideoxynucleotides labeled with 4 different fluorescent dyes; and finally (4) Hybridizing extended primers to a universal DNA array and determining the identity of the bases that extend each primer by hybridization pattern analysis. Our contributions include a study of multiplexing algorithms for SBE/SBH genotyping assays and preliminary experimental results showing the achievable tradeoffs between the number of array probes and primer length on one hand and the number of SNPs that can be assayed simultaneously on the other. Simulation results on datasets both randomly generated and extracted from the NCBI dbSNP database suggest that the SBE/SBH architecture provides a flexible and cost-effective alternative to genotyping assays currently used in the industry, enabling genotyping of up to hundreds of thousands of user-specified SNPs per assay.Comment: 19 page

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

CAD Tools for DNA Micro-Array Design, Manufacture and Application

Motivation: As the human genome project progresses and some microbial and eukaryotic genomes are recognized, numerous biotechnological processes have attracted increasing number of biologists, bioengineers and computer scientists recently. Biotechnological processes profoundly involve production and analysis of highthroughput experimental data. Numerous sequence libraries of DNA and protein structures of a large number of micro-organisms and a variety of other databases related to biology and chemistry are available. For example, microarray technology, a novel biotechnology, promises to monitor the whole genome at once, so that researchers can study the whole genome on the global level and have a better picture of the expressions among millions of genes simultaneously. Today, it is widely used in many fields- disease diagnosis, gene classification, gene regulatory network, and drug discovery. For example, designing organism specific microarray and analysis of experimental data require combining heterogeneous computational tools that usually differ in the data format; such as, GeneMark for ORF extraction, Promide for DNA probe selection, Chip for probe placement on microarray chip, BLAST to compare sequences, MEGA for phylogenetic analysis, and ClustalX for multiple alignments. Solution: Surprisingly enough, despite huge research efforts invested in DNA array applications, very few works are devoted to computer-aided optimization of DNA array design and manufacturing. Current design practices are dominated by ad-hoc heuristics incorporated in proprietary tools with unknown suboptimality. This will soon become a bottleneck for the new generation of high-density arrays, such as the ones currently being designed at Perlegen [109]. The goal of the already accomplished research was to develop highly scalable tools, with predictable runtime and quality, for cost-effective, computer-aided design and manufacturing of DNA probe arrays. We illustrate the utility of our approach by taking a concrete example of combining the design tools of microarray technology for Harpes B virus DNA data

The Chameleon Architecture for Streaming DSP Applications

We focus on architectures for streaming DSP applications such as wireless baseband processing and image processing. We aim at a single generic architecture that is capable of dealing with different DSP applications. This architecture has to be energy efficient and fault tolerant. We introduce a heterogeneous tiled architecture and present the details of a domain-specific reconfigurable tile processor called Montium. This reconfigurable processor has a small footprint (1.8 mm$^2$ in a 130 nm process), is power efficient and exploits the locality of reference principle. Reconfiguring the device is very fast, for example, loading the coefficients for a 200 tap FIR filter is done within 80 clock cycles. The tiles on the tiled architecture are connected to a Network-on-Chip (NoC) via a network interface (NI). Two NoCs have been developed: a packet-switched and a circuit-switched version. Both provide two types of services: guaranteed throughput (GT) and best effort (BE). For both NoCs estimates of power consumption are presented. The NI synchronizes data transfers, configures and starts/stops the tile processor. For dynamically mapping applications onto the tiled architecture, we introduce a run-time mapping tool

On-chip biosensing platforms based on gold and silicon optical nano-resonators

Point-of-care (POC) devices are compact, mobile and fast detection platforms expected to advance early diagnosis, treatment monitoring and personalized healthcare, and revolutionize today’s healthcare system, especially in remote areas. The need for POC devices strongly drives the development of novel biosensor technology. Building a small, fast, simple, and sensitive platform for biomolecule detection is a challenge that relies on the integration of multiple fields of expertise and engineering. Optical nanoresonators have shown great promise as label-free biosensors because of direct light coupling and sub-wavelength sensing modes. Metallic nanoresonators with localized surface plasmon resonances (LSPR) are already well studied and were proven a solid alternative to the commercialized surface plasmon resonance (SPR) sensors. More recently, dielectric nanoresonators have also gained traction due to the reduced losses and the ability to manipulate both the electric and magnetic components of the incident light. In this thesis, we advance the field of biosensing and use optical nanoresonators as operative platforms relevant for disease diagnosis and treatment monitoring. By combining different optimized optical nanoresonators, both metallic and dielectric, with state-of-the-art microfluidics and surface chemistry, we have developed and tested several detection platforms. We first focused on developing a microfluidic lab-on-chip device for multiplexed biosensing utilizing the LSPR of gold nanoresonator arrays. By simultaneously tracking the extinction of 32 sensor arrays, we demonstrated multiplexed quantitative detection of four breast cancer markers in human serum. We showed that with well-optimized immunoassays, a low limit of detection (LOD) can be reached, paving the way towards clinically-relevant POC devices. Additionally, we implemented silicon nanoresonators supporting Mie resonances into functional and clinically-relevant applications. By integrating several arrays of Si nanoresonators with state-of-the-art microfluidics, we demonstrated their ability to detect cancer markers in human serum with high sensitivity and high specificity. Furthermore, we showed that the fabrication of Si nanoresonator array using low cost and scalable projection lithography leads to sufficiently low limits of detection, while enabling cheaper and faster sensor production for future POC applications. We also investigated the respective role of electric and magnetic dipole resonances and showed that they are associated with two different transduction mechanisms: resonance redshift and extinction decrease. Our work advances the development of future point-of-care sensing platforms for fast and low cost health monitoring at the molecular scale.La instrumentación Point-of-care (POC) es compacta, móvil y permite una detección rápida, razón por la que se prevé que sean de gran ayuda en áreas como el diagnostico precoz, la monitorización de tratamientos y la medicina personalizada, revolucionando los modelos sanitarios, especialmente en las zonas de difícil acceso y con menos recursos. La necesidad de este tipo de dispositivos impulsa el desarrollo de novedosas tecnologías en el campo de los bio-sensores. Diseñar equipos para la detección de bio-moléculas que sean rápidos, pequeños y sencillos es un reto que requiere la integración de múltiples campos de la ciencia y la ingeniería. Los nano-resonadores ópticos muestran un gran potencial como bio-sensores sin necesidad de marcaje, gracias a su capacidad de acoplase directamente con la luz en modos menores que la longitud de onda. Los nano-resonadores metálicos basados en resonancias plasmónicas superficiales localizadas (LSPR) han sido estudiados y han demostrado ser una firme alternativa a los ya comerciales basados en resonancias plasmónicas superficiales (SPR). Los nano-resonadores dieléctricos han sido recientemente objeto de atención debido a sus bajas perdidas y la capacidad de manipular los componentes eléctricos y magnéticos de la luz. En esta tesis presentamos avances en el campo de la bio-detección y en el uso de los nano-resonadores ópticos como potenciales herramientas para la detección de enfermedades y monitorización de los tratamientos. Hemos desarrollado y evaluado distintas plataformas de detección combinando los nano-resonadores ópticos, tanto metálicos como dieléctricos, con las más avanzadas técnicas de microfluídica y química de superficies. En primer lugar, nos centramos en el desarrollo de un dispositivo microfluídico basado en sensores LSPR de oro que permite multiplexar 32 canales. Los 32 sensores se monitorizan en tiempo real para demostrar la cuantificación de 4 marcadores de cáncer de mama en suero sanguíneo humano. Demostramos que mediante la optimización de los ensayos se pueden alcanzar bajos límites de detección (LOD), lo que allana el camino hacia dispositivos POC de uso clínico. Por otro lado, hemos utilizado los nano-resonadores de silicio integrados con la microfluídica para también detectar marcadores de cáncer en suero. Estos sensores, cuyo principio de funcionamiento se basa en resonancias de MIE, han demostrado ser una alternativa razonable a los sensores de oro. Además, demostramos que un proceso de fabricación de nano-resonadores de silicio rápido, escalable y de bajo coste da lugar a límites de detección suficientes para la producción de futuras POC. También realizamos un minucioso estudio del rol de las resonancias eléctricas y magnéticas en dichos sensores y su relación con el desplazamiento y el cambio magnitud de la resonancia del sensor global. Nuestro trabajo es un avance en el desarrollo de futuros instrumentos POC rápidos y baratos en el ámbito de la salud a escala molecular.Postprint (published version

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

Development of Dendrimer-based Technologies for Phosphoproteomics and Glycoproteomics in Biomarker Discovery

The dynamics of post-translational modifications (PTMs) of proteins keeps cells adapting to the ever-changing microenvironment by regulating protein structure and function in the real-time mode. Of all PTMs, protein phosphorylation and glycosylation are undoubtedly two of the most common and important PTMs and have been demonstrated to be closely linked to the onset and progression of various human diseases. Our lab has been focusing on developing novel and more efficient technologies by taking advantage of the properties of dendrimers – a soluble nanopolymer with chemically well-defined structure and functional surface groups – to facilitate the detection and quantification of PTMs using several biochemical assays and mass spectrometry-based shotgun proteomics

Graphics processing unit accelerating compressed sensing photoacoustic computed tomography with total variation

Photoacoustic computed tomography with compressed sensing (CS-PACT) is a commonly used imaging strategy for sparse-sampling PACT. However, it is very time-consuming because of the iterative process involved in the image reconstruction. In this paper, we present a graphics processing unit (GPU)-based parallel computation framework for total-variation-based CS-PACT and adapted into a custom-made PACT system. Specifically, five compute-intensive operators are extracted from the iteration algorithm and are redesigned for parallel performance on a GPU. We achieved an image reconstruction speed 24–31 times faster than the CPU performance. We performed in vivo experiments on human hands to verify the feasibility of our developed method