Graph4Med: a web application and a graph database for visualizing and analyzing medical databases

Background: Medical databases normally contain large amounts of data in a variety of forms. Although they grant significant insights into diagnosis and treatment, implementing data exploration into current medical databases is challenging since these are often based on a relational schema and cannot be used to easily extract information for cohort analysis and visualization. As a consequence, valuable information regarding cohort distribution or patient similarity may be missed. With the rapid advancement of biomedical technologies, new forms of data from methods such as Next Generation Sequencing (NGS) or chromosome microarray (array CGH) are constantly being generated; hence it can be expected that the amount and complexity of medical data will rise and bring relational database systems to a limit. Description: We present Graph4Med, a web application that relies on a graph database obtained by transforming a relational database. Graph4Med provides a straightforward visualization and analysis of a selected patient cohort. Our use case is a database of pediatric Acute Lymphoblastic Leukemia (ALL). Along routine patients’ health records it also contains results of latest technologies such as NGS data. We developed a suitable graph data schema to convert the relational data into a graph data structure and store it in Neo4j. We used NeoDash to build a dashboard for querying and displaying patients’ cohort analysis. This way our tool (1) quickly displays the overview of patients’ cohort information such as distributions of gender, age, mutations (fusions), diagnosis; (2) provides mutation (fusion) based similarity search and display in a maneuverable graph; (3) generates an interactive graph of any selected patient and facilitates the identification of interesting patterns among patients. Conclusion: We demonstrate the feasibility and advantages of a graph database for storing and querying medical databases. Our dashboard allows a fast and interactive analysis and visualization of complex medical data. It is especially useful for patients similarity search based on mutations (fusions), of which vast amounts of data have been generated by NGS in recent years. It can discover relationships and patterns in patients cohorts that are normally hard to grasp. Expanding Graph4Med to more medical databases will bring novel insights into diagnostic and research

The Synthesis of Small Oligopeptides Containing Cysteine Residues

In regard to polypeptides, cysteine residues are composed of a sidechain group containing a thiol group responsible for the formation of disulfide bonds, which are covalent bonds that consist of two thiol groups linked together. In biological systems, disulfide bonds are imperative to forming many secondary and tertiary protein structures. One particular enzyme known as thioredoxin serves to control where these bonds form and ultimately catalyze oxidative protein folding. Furthermore, many neurodegenerative diseases such as Alzheimer\u27s and prions are linked to disulfide bond scrambling, which causes proteins to misfold. Research by our group has shown that the proximity of the cysteine residue with respect to the N-terminus and C-terminus is linked to the rate of which the disulfide bond forms. In order to understand the causes of different rates in disulfide bond formation, our lab has designed experiments to test the rates of disulfide formation among different peptides. Our research focuses on synthesizing small oligopeptides containing cysteine residues. The cysteine containing small oligopeptides were synthesized following the Solid Phase Peptide Synthesis protocol. This was done by linking amino acid residues together by beginning with the Rink Amide Resin through multiple rounds of deprotection, washing, coupling, and cleaving steps. The resulting peptides were purified by different techniques, followed by lyophilization, and confirmed through mass spectroscopy analysis. Overall, the main goal of our research is to synthesize small cysteine-containing peptides, analyze disulfide bonds between those small peptides, and to apply the findings to macro biological systems

Parallel Implementation Technique of Digital Equalizer for Ultra-High-Speed Wireline Receiver

This paper presents a parallel implementation technique of digital equalizer for high-speed wireline serial link receiver (RX). In wireline RX, inter-symbol interference (ISI) is mitigated by continuous-time linear equalizer, and the remaining ISI is cancelled out by decision-feedback equalizer (DFE). However, due to the existence of feedback loop in DFE, there is no trivial way to parallelize it, making it difficult to be realized in digital circuits for wireline RX based on analogto-digital converter (ADC) with ≥ 56 Gb/s data rate. In this work, convolution theorem is applied for achieving parallel digital equalizer implementation. The digital equalizer datapath consists of discrete Fourier transform (DFT) core, inverse-DFT (IDFT) core, complex multipliers between DFT and IDFT cores, and overlap-add circuit. Design considerations for low-area VLSI implementation of such architecture is discussed

A 5Gb/s 7.1fJ/b/mm 8× Multi-Drop On-Chip 10mm Data Link in 14nm FinFET CMOS SOI at 0.5V

© 2017 JSAP. We report a 5Gb/s data link implemented in 14nm FinFET CMOS SOI technology in which a single transmitter (TX) broadcasts NRZ data to eight receivers (RXs) distributed along an on-chip RC-dominated 10mm-long channel. The TX comprises a full-rate AC-coupled 2-tap FIR driver with a quarter-rate pre-driver. Each RX is equipped with a novel decision-gated 1-tap speculative DFE optimized for low-power. The RX architecture is half-rate and sliced data are de-multiplexed at quarter-rate. PRBS generator and checker are available on-chip. Correct operation was verified with PRBS31 data transmitted at 5Gb/s and concurrently received error-free at each drop with >40% horizontal margin (BER<10-12). At this data-rate the efficiency is 7.1fJ/b/mm' resulting in the best performance among multi-drop on-chip data links so far published (to the best of our knowledge). The TX and eight RXs are running on a 0.5 V power supply and consume 0.62 and 0.98mW' respectively.status: publishe

Design Techniques for High-Speed Multi-Level Viterbi Detectors and Trellis-Coded-Modulation Decoders

The implementation of a 25.6-Gb/s four-level pulse-amplitude-modulation (4-PAM) reduced-state sliding-block Viterbi detector (VD) is presented. The power consumption of the VD is 105 orilV at a supply voltage of 0.7 V, corresponding to an energy efficiency of 4.1 pJ/b. A data rate of 30.4 Gb/s is achieved with an energy efficiency of 5.3 pith at a supply voltage of 0.8 V. The VD, implemented in an experimental chip fabricated in 14-nm CMOS FINFET, exploits set-partitioning principles and embedded per-survivor decision feedback to reduce implementation complexity and power consumption. The active area of the VD with 12 slices, each operating at one-eighth of the modulation rate, is 0.507 x 0.717 mm(2). Experimental results showing system performance are obtained by using a (2(15)-1)-bit pseudo-random binary sequence. The impact of the synchronization length and survivor path memory length on the detector design and system performance are shown. A new pipelined reduced-state sequence detector algorithm is presented for high-speed implementations. A novel speculative symbol timing recovery scheme is proposed. New simulation results are obtained to compare the performance of the Reed-Solomon (RS)-encoded 4-PAM scheme with that of the concatenated RS 4-D 5-PAM trellis-coded-modulation (TCM) scheme over an ideal band-limited additive-white-Gaussian-noise channel. Drawing on the results achieved for the VD, novel design techniques for a high-speed low-complexity eight-state 4-D 5-PAM TCM decoder is proposed