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ieee International conference on Nano/Micro Engineered and Molecular systems (NEMS)

作者： Annesha Mazumder Syed Azeemuddin Tapan K. Sau Prabhakar Bhimalapuram CVEST International Institute of Information Technology (IIIT) Hyderabad Telangana India Center for Bioinformatics International Institute of Information Technology (IIIT) Hyderabad Telangana India

ISBN: (数字)9781728172309

ISBN: (纸本)9781728172316

Radio Frequency (RF) based sensors have shown great potential for the qualitative and quantitative analysis of different chemical and biological entities. In this work, the feasibility of performing RF based sensing by using gold particles has been explored with the help of the computational tool, HFSS (High Frequency Structure Simulator). The analysis is performed for an Interdigitated Capacitor based sensor. Various physical parameters of cylindrical gold particles such as radius and thickness have been varied, and the electrical parameters of the sensor systems have been studied. In particular, the reflection coefficients have been determined for various cases. In addition to the physical parameters, different configurations of the gold particles such as their linear and non-linear arrangements have been analyzed. The analyses offer promising results for the development of efficient sensing platforms.

关键词： Sensors Gold Resonant frequency Radio frequency Finite element analysis Sensor phenomena and characterization Nanobioscience

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AlignS: A Processing-In-Memory Accelerator for DNA Short Read Alignment Leveraging SOT-MRAM 19

AlignS: A Processing-In-Memory Accelerator for DNA Short Rea...

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56th ACM/EDAC/ieee Design Automation conference (DAC)

作者： Angizi, Shaahin Sun, Jiao Zhang, Wei Fan, Deliang Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA Univ Cent Florida Dept Comp Sci Orlando FL 32816 USA

ISBN: (纸本)9781450367257

Classified as a complex big data analytics problem, DNA short read alignment serves as a major sequential bottleneck to massive amounts of data generated by next-generation sequencing platforms. With Von-Neumann computing architectures struggling to address such computationally-expensive and memory-intensive task today, Processing-in-Memory (PIM) platforms are gaining growing interests. In this paper, an energy-efficient and parallel PIM accelerator (AlignS) is proposed to execute DNA short read alignment based on an optimized and hardware-friendly alignment algorithm. We first develop AlignS platform that harnesses SOT-MRAM as computational memory and transforms it to a fundamental processing unit for short read alignment. Accordingly, we present a novel, customized, highly parallel read alignment algorithm that only seeks the proposed simple and parallel in-memory operations (i.e. comparisons and additions). AlignS is then optimized through a new correlated data partitioning and mapping methodology that allows local storage and processing of DNA sequence to fully exploit the algorithm-level's parallelism, and to accelerate both exact and inexact matches. The device-to-architecture co-simulation results show that AlignS improves the short read alignment throughput per Watt per mm(2) by similar to 12x compared to the ASIC accelerator. Compared to recent FM-index-based ReRAM platform, AlignS achieves 1.6x higher throughput per Watt.

关键词： DNA Computer architecture Genomics Sequential analysis Magnetic tunneling bioinformatics Micromechanical devices

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Identification of Cancer Development Related Pathways Based on Co-Expression Analyses

Identification of Cancer Development Related Pathways Based ...

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ieee International conference on bioinformatics and Biomedicine (BIBM)

作者： Hongyang Jiang Zhihang Wang Chaoyi Yin Peishuo Sun Ying Xu Huiyan Sun School of Artificial Intelligence Jilin University Changchun Innovation Group of Marine Engineering Materials and Corrosion Control Southern Marine Science and Engineering Guangdong Laboratory Zhuhai China College of Computer Science and Technology Jilin University Changchun China School of Artificial Intelligence Jilin University Changchun China Computational Systems Biology Lab Institute of Bioinformatics University of Georgia Athens USA School of Artificial Intelligence Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Cancer is a rapidly evolving disease, with complex physiological changes throughout its development. Different patients of the same cancer type may require distinct treatments depending on the level of development. Hence it is essential to identify the genes and biological processes strongly associated with cancer progression to design an effective treatment plan. Our study has found that cancer samples of the same development stage (or grade, subtype) tend to share highly unique co-expression patterns, providing considerably stronger discerning power than differential expressions for cancer staging (and grading, subtyping). Based on this, we have developed a framework for identification and analyses of genes and pathways strongly associated with a cancer's development through identification of co-expression patterns that become increasingly stronger or weaker over cancer samples from early through advanced stages. Functional analyses of such co-expressed genes reveal that (1) cell-cycle, immune response, ribosome, proteasome and oxidative phosphorylation, among others, strongly associate with cancer development, (2) the co-expression patterns among ribosome, proteasome and oxidative phosphorylation genes tend to become increasingly weaker as a cancer advances, for almost all cancer types, and (3) the co-expression patterns among cell cycle and immune response genes tend to become increasingly stronger with cancer progression. We anticipate that co-expression-based analyses like we present here will become a key technique for functional studies of cancer development and evolution.

关键词： Cancer Correlation Indexes Biological processes Physiology Immune system Genetic expression

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Guest Editorial for Special Section on BIBM 2015

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第6期15卷 1752-1753页

作者： Tian, Tianhai Huang, Jingshan Monash Univ Sch Math Sci Melbourne Vic 3800 Australia Univ S Alabama Sch Comp Shelby HallSuite 2101150 Jaguar Dr Mobile AL 36688 USA

The six papers in this special section were presented at the ieee BIBM 2015 conference that was held in Washington, D.C., November 9-12, 2015. The scientific program highlighted five themes to provide breadth, depth, and synergy for research collaboration: 1 genomics and molecular structure, function, and evolution; 2 computational systems biology; 3 medical informatics and translational bioinformatics; 4 cross-cutting computational methods and bioinformatics infrastructures; and 5 healthcare informatics,

关键词： Special issues and sections Meetings bioinformatics Informatics Biological systems modeling Genomics computational modeling

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ieee Access Special Section Editorial: Scalable Deep Learning for Big Data

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ieee ACCESS 2020年 8卷 216617-216622页

作者： Han, Liangxiu Zhang, Daoqiang Rana, Omer Pan, Yi Jabbar, Sohail Yousif, Mazin Aloqaily, Moayad Manchester Metropolitan Univ Dept Comp & Math Manchester M1 5GD Lancs England Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 210016 Peoples R China Cardiff Univ Sch Comp Sci & Informat Cardiff CF24 3AA Wales Georgia State Univ Dept Comp Sci Atlanta GA 30302 USA Univ Faisalabad Dept Computat Sci Faisalabad 38000 Pakistan DXC Technol Tysons VA 22102 USA Al Ain Univ Fac Engn Al Ain U Arab Emirates

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Guest Editors' Introduction to the Special Section on the 14th International conference on computational Methods in systems Biology (CMSB 2016)

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第4期15卷 1122-1123页

作者： Bartocci, Ezio Lio, Pietro Paoletti, Nicola Vienna Univ Technol Fac Informat Treitlstr 3 A-1040 Vienna Austria Univ Cambridge Dept Comp Sci & Technol William Gates Bldg15 JJ Thomson Ave Cambridge CB3 0FD England SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA

No abstract available.

关键词： Special issues and sections Meetings computational biology

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Guest Editorial for Special Section on the 12th International conference on Intelligent Computing (ICIC)

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第5期15卷 1433-1435页

作者： Huang, De-Shuang Bevilacqua, Vitoantonio Gromiha, M. Michael Tongji Univ Machine Learning & Syst Biol Lab Shanghai 201804 Peoples R China Polytech Bari Elect & Informat Engn Dept I-70126 Bari BA Italy Indian Inst Technol IIT Madras Dept Biotechnol Madras 600036 Tamil Nadu India

The eight papers included in this special section were presented at the 12th International conference on Intelligent Computing (ICIC) held at Lanzhou, China, during August 2-5, 2016. ICIC was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the multifaceted aspects of intelligent computing.

关键词： Special issues and sections Meetings bioinformatics Machine learning Intelligent systems

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11th Asian conference on Intelligent Information and Database systems, ACIIDS 2019

11th Asian Conference on Intelligent Information and Databas...

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11th Asian conference on Intelligent Information and Database systems, ACIIDS 2019

ISBN: (纸本)9783030147983

The proceedings contain 124 papers. The special focus in this conference is on Intelligent Information and Database systems. The topics include: Word Mover’s Distance for Agglomerative Short Text Clustering;improving Semantic Relation Extraction System with Compositional Dependency Unit on Enriched Shortest Dependency Path;an Adversarial Learning and Canonical Correlation Analysis Based Cross-Modal Retrieval Model;event Prediction Based on Causality Reasoning;a Method for Detecting and Analyzing the Sentiment of Tweets Containing Conditional Sentences;aggregating Web Search Results;cross-Lingual Korean Speech-to-Text Summarization;on Some Approach to Evaluation in Personalized Document Retrieval systems;a Class-Cluster k-Nearest Neighbors Method for Temporal In-Trouble Student Identification;a Formal Framework for the Ontology Evolution;multidimensional Permutation Entropy for Constrained Motif Discovery;A LSTM Approach for Sales Forecasting of Goods with Short-Term Demands in E-Commerce;detection of Rare Elements in Investigation of Medical Problems;Cardiac Murmur Effects on Automatic Segmentation of ECG Signals for Biometric Identification: Preliminary Study;an Approach to Estimation of Residential Housing Type Based on the Analysis of Parked Cars;household Electric Load Pattern Consumption Enhanced Simulation by Random Behavior;anomaly Detection Procedures in a Real World Dataset by Using Deep-Learning Approaches;Developing a General Video Game AI Controller Based on an Evolutionary Approach;separable Data Aggregation by Layers of Binary Classifiers;adaptation and Recovery Stages for Case-Based Reasoning systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors;logical Problem Solving Framework;Feature Extraction Analysis for Emotion Recognition from ICEEMD of Multimodal Physiological Signals;selected Problems of Controllability of Semilinear Fractional systems-A Survey.

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Evaluating Workflow Management systems: A bioinformatics Use Case

Evaluating Workflow Management Systems: A Bioinformatics Use...

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2018 ieee International conference on bioinformatics and Biomedicine, BIBM 2018

作者： Larsonneur, Elise Mercier, Jonathan Wiart, Nicolas Floch, Edith Le Delhomme, Olivier Meyer, Vincent Institut de Biologie Francois Jacob CEA Université Paris-Saclay EvryF-91057 France

ISBN: (纸本)9781538654880

Biological knowledge discovery is a tedious task which relies on computationally intensive analyses to process huge volumes of data and metadata. This task can be facilitated by a well-designed workflow management system, capable of deploying and efficiently orchestrating the scientific analysis. However choosing the right workflow management system remains a critical challenge. In this study, we propose ten metrics for evaluating the efficiency of workflow management systems, and show how the Pegasus-mpi-cluster and Snakemake workflow management systems gave the best overall performance, closely followed by Nextflow. © 2018 ieee.

关键词： bioinformatics

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Towards Reproducible bioinformatics: The OpenBio-C Scientific Workflow Environment

Towards Reproducible Bioinformatics: The OpenBio-C Scientifi...

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ieee Symposium on bioinformatics and Bioengineering (BIBE)

作者： Alexandros Kanterakis Galateia Iatraki Konstantina Pityanou Lefteris Koumakis Nikos Kanakaris Nikos Karacapilidis George Potamias Foundation for Research and Technology-Hellas (FORTH) Institute of Computer Science Heraklion Greece Dept. of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Crete Greece Industrial Management and Information Systems Lab MEAD University of Patras Patras Greece

ISBN: (纸本)9781728146188

The highly competitive environment of post-genomics biomedical research is pushing towards the production of highly qualified results and their utilization in clinical practice. Due to this pressure, an important factor of scientific progress has been underestimated namely, the reproducibility of the results. To this end, it is critical to design and implement computational platforms that enable seamless and unhindered access to distributed bio-data, software and computational infrastructures. Furthermore, the need to support collaboration and form synergistic activities between the engaged researchers is also raised, as the mean to achieve consensus on respective scientific discoveries. The aforementioned needs and requirements underlie the motivations for the development of OpenBio-C workflow environment, and determine its fundamental objectives. The insufficiencies of current workflow editing and execution environments are explored, and the key-directions to advance over an environment that supports reproducibility are stated. The basic components and functionality of the OpenBio-C initial implementation (beta version) are detailed.

关键词： bioinformatics Tools Collaboration Pipelines Genomics Market research Semantics

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