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ieee International conference on Data Mining (ICDM)

作者： Yan Li Lu Wang Jie Wang Jieping Ye Chandan K. Reddy Dept. of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI Dept. of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI Dept. of Computer Science Wayne State University Detroit MI Dept. of Computer Science Virginia Tech Arlington VA

ISBN: (纸本)9781509054749

In survival analysis, the primary goal is to monitor several entities and model the occurrence of a particular event of interest. In such applications, it is quite often the case that the event of interest may not always be observed during the study period and this gives rise to the problem of censoring which cannot be easily handled in the standard regression approaches. In addition, obtaining sufficient labeled training instances for learning a robust prediction model is a very time consuming process and can be extremely difficult in practice. In this paper, we propose a transfer learning based Cox method, called Transfer-Cox, which uses auxiliary data to augment learning when there are insufficient amount of training examples. The proposed method aims to extract "useful" knowledge from the source domain and transfer it to the target domain, thus potentially improving the prediction performance in such time-to-event data. The proposed method uses the l 2,1 -norm penalty to encourage multiple predictors to share similar sparsity patterns, thus learns a shared representation across source and target domains, potentially improving the model performance on the target task. To speedup the computation, we apply the screening approach and extend the strong rule to sparse survival analysis models in multiple high-dimensional censored datasets. We demonstrate the performance of the proposed transfer learning method using several synthetic and high-dimensional microarray gene expression benchmark datasets and compare with other related competing state-of-the-art methods. Our results show that the proposed screening approach significantly improves the computational efficiency of the proposed algorithm without compromising the prediction performance. We also demonstrate the scalability of the proposed approach and show that the time taken to obtain the results is linear with respect to both the number of instances and features.

关键词： Analytical models Learning systems Data models Hazards Predictive models Prediction algorithms Standards

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Behavior and Depression Gene Networks Reconstruction and Analysis

Behavior and Depression Gene Networks Reconstruction and Ana...

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ieee Region 8 International conference on computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： R.A. Ivanov V.I. Zamyatin A.I. Klimenko T.N. Astakhova Y.G. Matushkin A.N. Savostyanov S.A. Lashin Sector for bioinformatics and information technologies in genetics Institute of Cytology and Genetics SB RAS Novosibirsk State University Novosibirsk Russian Federation Laboratory of Biological Markers of Human Social Behavior Humanitarian Institute Novosibirsk State University Novosibirsk Russian Federation Laboratory of Molecular-Genetic Systems Institute of Cytology and Genetics Novosibirsk Russian Federation Laboratory of Psychological Genetics Institute of Cytology and Genetics Laboratory of Differential Psychophysiology Institute of Physiology and Basic Medicine Novosibirsk Russian Federation

One of the main interests of modern neurophysiology is aimed at studying biology bases of anxiety and depression. The unsolved problem is complex integration between heredity factors, indexes of the brain electrical activity and psychological traits of people. Neurobiological understanding of this topic is essential not only for identification of genes involved in molecular mechanisms of depression, but also for knowledge of complex relationship of these genes. Research of these interactions could contribute to development of new prevention, diagnosis and treatment methods of depression. In our research, we reconstruct several PPI networks and networks of transcriptional regulation as well, in order to build the model of complex interaction of environmental and heredity factors of vulnerability to depression and other mental disorders. We identify the number of genes, which expression is supposedly related to environmental factors, for further experimental verification.

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Accomplishments and Challenges of Protein Ontology

Accomplishments and Challenges of Protein Ontology

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ieee Annual International Computer Software and Applications conference (COMPSAC)

作者： E. Chang F.K. Hussain T.S. Dillon A.S. Sidhu Fac. of Inf. Technol. Technol. Sydney Univ. NSW

Recent progress in proteomics, computational biology, and ontology development has presented an opportunity to investigate protein data sources from a unique perspective that is, examining protein data sources through structure and hierarchy of protein ontology (PO). Various data mining algorithms and mathematical models provide methods for analyzing protein data sources; however, there are two issues that need to be addressed: (1) the need for standards for defining protein data description and exchange and (2) eliminating errors which arise with the data integration methodologies for complex queries. Protein ontology is designed to meet these needs by providing a structured protein data specification for protein data representation. Protein ontology is a standard for representing protein data in a way that helps in defining data integration and data mining models for protein structure and function. We report here our development of PO; a semantic heterogeneity framework based on relationships between PO concepts; and analysis of resultant PO data of human proteins. We also talk in this paper briefly about our ongoing work of designing a trustworthy framework around PO

关键词： Ontologies Protein engineering Databases Biology Australia Data mining bioinformatics Information technology Information systems Proteomics

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Hardware image assessment for wireless endoscopy capsules

Hardware image assessment for wireless endoscopy capsules

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Annual International conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： M. A. Khorsandi N. Karimi S. Samavi M. Hajabdollahi S. M.R. Soroushmehr K. Ward K. Najarían Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran Department of Emergency Medicine University of Michigan Ann Arbor U.S.A. Michigan Center for Integrative Research in Critical Care Emergency Medicine Department University of Michigan Ann Arbor U.S.A. Department of Computational Medicine and Bioinformatics Department of Emergency Medicine Michigan Center for Integrative Research in Critical Care University of Michigan Ann Arbor U.S.A.

ISBN: (纸本)9781457702198

Wireless capsule endoscopy is a new technology in the realm of telemedicine that has many advantages over the traditional endoscopy systems. Transmitted images should help diagnosis of diseases of the gastrointestinal tract. Two important technical challenges for the manufacturers of these capsules are power consumption and size of the circuitry. Also, the system must be fast enough for real-time processing of image or video data. To solve this problem, many hardware designs have been proposed for implementation of the image processing unit. In this paper we propose an architecture that could be used for the assessment of endoscopy images. The assessment allows avoidance of transmission of medically useless images. Hence, volume of data is reduced for more efficient transmission of images by the endoscopy capsule. This is done by color space conversion and moment calculation of images captured by the capsule. The inputs of the proposed architecture are RGB image frames and the outputs are images with converted colors and calculated image moments. Experimental results indicate that the proposed architecture has low complexity and is appropriate for a real-time application.

关键词： Image color analysis Hardware Computer architecture Endoscopes Power demand Pipelines Wireless sensor networks

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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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A Multibody Atomic Statistical Potential for the Prediction of Enzyme-Inhibitor Binding Energy

A Multibody Atomic Statistical Potential for the Prediction ...

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Annual International conference of the ieee Engineering in Medicine and Biology Society

作者： Majid Masso the Laboratory for Structural Bioinformatics School of Systems Biology George Mason University Manassas VA 20110 USA

ISBN: (纸本)9781424441198

Accurate prediction of enzyme-inhibitor binding energy has the capacity to speed drug design and chemical genomics efforts by helping to narrow the focus of experiments. Here a non-redundant set of three hundred high-resolution crystallographic enzyme-inhibitor structures was compiled for analysis, complexes with known binding energies (ΔG) based on the availability of experimentally determined inhibition constants (ki). Additionally, a separate set of over 1400 diverse high-resolution macromolecular crystal structures was collected for the purpose of creating an all-atom knowledgebased statistical potential, via application of the Delaunay tessellation computational geometry technique. Next, two hundred of the enzyme-inhibitor complexes were randomly selected to develop a model for predicting binding energy, first by tessellating structures of the complexes as well as the enzymes without their bound inhibitors, then by using the statistical potential to calculate a topological score for each structure tessellation. We derived as a predictor of binding energy an empirical linear function of the difference between topological scores for a complex and its isolated enzyme. A correlation coefficient (r) of 0.79 was obtained for the experimental and calculated ΔG values, with a standard error of 2.34 kcal/mol. Lastly, the model was evaluated with the heldout set of one hundred complexes, for which structure tessellations were performed in order to calculate topological score differences, and binding energy predictions were generated from the derived linear function. Calculated binding energies for the test data also compared well with their experimental counterparts, displaying a correlation coefficient of r = 0.77 with a standard error of 2.50 kcal/mol.

关键词： A Multibody Atomic Enzyme-Inhibitor the heldout set

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Human CODIS STR loci profiling from HTS data

Human CODIS STR loci profiling from HTS data

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ieee conference on Technologies for Homeland Security

作者： Darrell O. Ricke Martha Petrovick Johanna Bobrow Tara Boettcher Christina Zook James Harper Edward Wack Eric Schwoebel Bioengineering Systems and Technologies Massachusetts Institute of Technology Lexington MA USA

ISBN: (纸本)9781509007714

Human DNA identification is currently performed by amplifying a small, defined set of short tandem repeat (STR) loci (e.g. CODIS) and analyzing the size of the alleles present at those loci by capillary electrophoresis. High-throughput DNA sequencing (HTS) could enable the simultaneous analysis of many additional STR and single nucleotide polymorphism (SNP) loci, improving accuracy and discrimination. However, it is necessary to demonstrate that HTS can generate accurate data on the CODIS loci to enable backwards compatibility with the FBI NDIS database. Sequencing can also detect novel polymorphisms within alleles that migrate with identical sizes by capillary electrophoresis, improving allele discrimination, and enhancing human identification analysis. All CODIS alleles from an individual can be amplified in a single, multiplex PCR reaction, and combined with additional barcoded samples prior to sequencing. A computational tool for allele identification from multiplexed sequence data has been developed. With longer-read-length platforms, 99.6% allele calling accuracy can be achieved. In the course of STR sequencing protocol development, 12 novel allele sequences have been identified for multiple loci. Sequencing STR loci combined with SNPs will enable new forensic applications.

关键词： Sequential analysis DNA Forensics Multiplexing Protocols bioinformatics High-temperature superconductors

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Quantifying statistics of gene product copy-number fluctuations: A stochastic hybrid systems approach

Quantifying statistics of gene product copy-number fluctuati...

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ieee conference on Decision and Control

作者： Zahra Vahdat Abhyudai Singh Department of Electrical and Computer Engineering University of Delaware Newark DE USA Department of Electrical and Computer Engineering Biomedical Engineering Mathematical Sciences Center for Bioinformatics and Computational Biology University of Delaware Newark DE USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Across diverse cell types, genes are often expressed at low levels resulting in significant stochastic fluctuations (noise) in intracellular copy number of mRNAs and proteins over time. Motivated by single-cell experiments, we capture this stochasticity by considering a given gene that toggles between transcriptionally active and inactive states with the time spent in each state being an arbitrary random variable. mRNAs are synthesized from the active state as per a Poisson process and each molecule degrades after a random lifespan (i.e., random time from birth to death). Modeling this process using the Stochastic Hybrid System (SHS) formalism we derive exact analytical results for the statistical moments of molecular counts. Our results show that for fixed mean mRNA numbers, fluctuations in mRNA levels are amplified with decreasing noise in mRNA lifespan. Relaxing the Poisson process assumption, we next consider a scenario where transcription events occur such that the time between successive events is an arbitrarily distributed random variable. In this case, we show that decreasing noise in mRNA lifespan can both increase/decrease mRNA count fluctuations depending on the underlying transcriptional process. Finally, we extend these results to the protein level, where increasing noise in mRNA counts is sometimes associated with decreasing noise in protein copy numbers.

关键词： Proteins Analytical models Fluctuations Exponential distribution Noise Stochastic processes Information processing Random variables Timing Kinetic theory

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A medical decision support system proposal supported by genomic analysis

A medical decision support system proposal supported by geno...

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ieee Signal Processing and Communications Applications (SIU)

作者： M. Erdem Çorapçioğlu Hasan Oğul Bilgisayar Mühendisliği Başkent Üniversitesi Ankara TÜRKİYE

It is known that, existing knowledge and experience have a key role in decision making process. This statement is more than true for a physician who is responsible for identifying diseases and executing the related medical treatment for patients. It is known that, regardless of the decision maker may not be able to execute correct decision if there is one or more condition that will affect the decision-making process. Whatever the circumstances, erroneous decision-making can lead to irreparable results in the medical field. Recent advancements in computational analysis showed that gene expressions can be used to identify both similar cases and assign experiments to related classes. Lately, it has found that, MicroRNA which consist of 21 to 23 nucleotides, has an important role in the regulation of gene expressions. In addition to this, there are several experiments which have shown that MicroRNA gene expression can be related with diseases and gene regulations. Personalized medical researches and practices have become very important in the recent period. Also, it is known that genetic analysis has a key role in personalized medical research. In this study, we propose a system which is using gene expression analysis to support medical decision support process.

关键词： bioinformatics Genomics Gene expression Decision making Cancer Decision support systems RNA

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Duck Eggs Hatching Procedure with A Low Cost User Convenient Integrated Device for Developing Countries

Duck Eggs Hatching Procedure with A Low Cost User Convenient...

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ieee Region 10 Humanitarian Technology conference (R10-HTC)

作者： Eftakhar Hossain Mohammad Zeyad S.M. Masum Ahmed Md Sadik Tasrif Anubhove Energy and Technology Research Division Advanced Bioinformatics Computational Biology and Data Science Laboratory Bangladesh Chattogram Bangladesh Erasmus+ Joint MSC in Smart Cities and Communities University of the Basque Country (UPV/EHU) Bilbao Spain

Poultry agriculture is a form of livestock farming that involves raising chickens, turkeys, ducks, etc, and raises them to provide eggs or meat. However, this work sheds light on the method of hatching duck eggs which maintains a suitable environment around the eggs through an automated and low cost device by controlling temperature (T) and relative humidity (RH). This paper presents a control strategy for automatic temperature and relative humidity control systems for the egg/s hatching procedure for rural areas people or unprivileged communities in the developing countries. One of the best outcomes of this work is the proper hatching procedure steps shown from the beginning to the end. Moreover, for a better understanding and outcomes, the research work has been done under a poultry farm in Charsita village, Lakshmipur, Bangladesh for 6 consecutive months of 2020. The experiment (egg/s hatching) has been conducted under an ice-box. Furthermore, a microcontroller (ATmega328p) is used to monitor the temperature and relative humidity by receiving data from the sensor DHT22 and manipulating the appropriate temperature and humidity using a logic algorithm code. Egg/s need a constant temperature and relative humidity of 35.6 °C to 37.8 °C and 60% to 80%, respectively. Nonetheless, an LCD (16*2) with a matrix keypad (4*4) has been integrated into the unit, allowing farmers to easily set, run, and monitor the appropriate temperature and relative humidity levels within the ice-box. Finally, the results of sensor testing, system device management, and performance rates are recorded to ensure the research's success.

关键词： Temperature sensors Temperature measurement Temperature distribution Costs Rural areas Humidity Developing countries

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