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Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) : Jeddah, Kingdom of Saudi Arabia. 30 November - 3 December 2015

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BMC genomics 2016年第6期17 Suppl 6卷 487页

作者： Jerry W. Shay Noriko Homma Ruyun Zhou Muhammad Imran Naseer Adeel G. Chaudhary Mohammed Al-Qahtani Nobutaka Hirokawa Maryam Goudarzi Albert J. Fornace Saleh Baeesa Deema Hussain Mohammed Bangash Fahad Alghamdi Hans-Juergen Schulten Angel Carracedo Ishaq Khan Hanadi Qashqari Nawal Madkhali Mohamad Saka Kulvinder S. Saini Awatif Jamal Jaudah Al-Maghrabi Adel Abuzenadah Adeel Chaudhary Mohammed Al Qahtani Ghazi Damanhouri Heba Alkhatabi Anne Goodeve Laura Crookes Nikolas Niksic Nicholas Beauchamp Adel M. Abuzenadah Jim Vaught Bruce Budowle Mourad Assidi Abdelbaset Buhmeida Leena Merdad Sudhir Kumar Sayaka Miura Karen Gomez Mahmood Rasool Ahmed Rebai Sajjad Karim Hend F. Nour Eldin Heba Abusamra Elham M. Alhathli Nada Salem Mohammed H. Al-Qahtani Hossam Faheem Ashok Agarwa Eberhard Nieschlag Joachim Wistuba Oliver S. Damm Mohd A. Beg Taha A. Abdel-Meguid Hisham A. Mosli Osama S. Bajouh Serdar Coskun Muhammad Abu-Elmagd Ashraf Dallol Sahar Hakamy Wejdan Al-Qahtani Asia Al-Harbi Shireen Hussain Burak Ozkosem Rick DuBois Safia S. Messaoudi Maryam T. Dandana Touhami Mahjoub Wassim Y. Almawi S. Abdalla M. Nabil Al-Aama Asmaa Elzawahry Tsuyoshi Takahashi Sachiyo Mimaki Eisaku Furukawa Rie Nakatsuka Isao Kurosaka Takahiko Nishigaki Hiromi Nakamura Satoshi Serada Tetsuji Naka Seiichi Hirota Tatsuhiro Shibata Katsuya Tsuchihara Toshirou Nishida Mamoru Kato Sajid Mehmood Naeem Mahmood Ashraf Awais Asif Muhammad Bilal Malik Siddique Mehmood Aadil Hussain Qazi Mohammad Sajid Jamal Mughees Uddin Siddiqui Mohammad A. Alzohairy Mohammad A. Al Karaawi Taoufik Nedjadi Heba Al-Khattabi Adel Al-Ammari Ahmed Al-Sayyad Hédia Zitouni Nozha Raguema Marwa Ben Ali Wided Malah Raja Lfalah Wassim Almawi Mohammed Elanbari Andrey Ptitsyn Sana Mahjoub Rabeb El Ghali Bechir Achour Nidhal Ben Amor Brahim N’siri Hamid Morjani Esam Azhar Vera Chayeb Maryam Dendena Hedia Zitouni Khedija Zouari-Limayem Bassem Refaat Ahmed M. Ashshi Sarah A. Batwa Hazem Ramadan Amal Awad Ahmed Ateya Adel Galal Ahmed El-Shemi Ahmad Ashshi Mohammed Basalamah Youjin Na Cha University of Texas Southwestern Medical Center Dallas USA Department of Cell Biology and Anatomy Graduate School of Medicine the University of Tokyo Tokyo Japan Center of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Department of Biochemistry and Molecular & Cellular Biology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Oncology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Radiation Medicine Lombardi Comprehensive Cancer Center Georgetown University Washington USA Center of Excellence in Genomic Medicine Research (CEGMR) King Abdulaziz University Jeddah Kingdom of Saudi Arabia King Fahd Medical Research Centre King Abdulaziz University Jeddah Saudi Arabia Centre of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Sheffield Diagnostic Genetic Service Sheffield Children’s NHS Foundation Trust Western Bank Sheffield UK Center of Innovations in Personalized Medicine King Abdulaziz University Jeddah Saudi Arabia President ISBER Editor-in-Chief Biopreservation & Biobanking ᅟ USA Institute of Applied Genetics Department of Molecular and Medical Genetics University of North Texas Health Science Center Fort Worth USA Department of Dental Public Health Faculty of Dentistry King Abdulaziz University Jeddah Saudi Arabia Institute for Genomics and Evolutionary Medicine Temple University Philadelphia USA Center of Excellence in Genomic Medicine King Abdulaziz University Jeddah Kingdom of Saudi Arabia Laboratory of Molecular and Cellular Screening Processes (Bioinformatics Group) Centre of Biotechnology of Sfax Sfax Tunisia Fujitsu Technology Solutions International ᅟ ᅟ Case Western Reserve University School of Medicine and Lerner College of Medicine Cleveland Clinic Foundation Cleveland USA American Center for Reproductive Medicine Andrology Center Cleveland USA Center for Reproductive Medicine and

O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa O3 Integration of metagenomics and metabolomics in gut microbiome research Maryam Goudarzi, Albert J. Fornace Jr. O4 A unique integrated system to discern pathogenesis of central nervous system tumors Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis Heba Alkhatabi O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp O7 Targeted sequencing panels and their utilization in personalized medicine Adel M. Abuzenadah O8 International biobanking in the era of precision medicine Jim Vaught O9 Biobank and biodata for clinical and forensic applications Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors Jaudah Al-Maghrabi O11 The CEGMR biobanking unit: achievements, challenges and future plans Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad O12 Phylomedicine of tumors Sudhir Kumar, Sayaka Miura, Karen Gomez O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment Angel Carracedo, Mahmood Rasool O14 From association to causality: translation of GWAS findings for genomic me

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Hardware Particle Swarm Optimization with passive congregation for embedded applications

Hardware Particle Swarm Optimization with passive congregati...

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Southern Conference on programmable Logic

作者： Daniel M. Muñoz Carlos H. Llanos Leandro dos S. Coelho Mauricio Ayala-Rincón Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Paraná Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brazil

Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power consumption and portability must be accomplished. This paper proposes a hardware implementation of the Particle Swarm Optimization algorithm with passive congregation (HPPSOpc), which was developed using several floating-point arithmetic libraries. The passive congregation is a biological behavior which allows the swarm to preserve its integrity, balancing between global and local search. The HPPSOpc architecture was implemented on a Virtex5 FPGA device and validated using two multimodal benchmark problems. Synthesis, simulation and execution time results demonstrates that the passive congregation approach is a low cost solution for solving embedded optimization problems with a high performance.

关键词： Hardware Computer architecture Software Field programmable gate arrays Benchmark testing Optimization Software algorithms

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Opposition-based shuffled PSO with passive congregation applied to FM matching synthesis

Opposition-based shuffled PSO with passive congregation appl...

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Congress on Evolutionary Computation

作者： Daniel M. Muñoz Carlos H. Llanos Leandro dos S. Coelho Mauricio Ayala-Rincón Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia Brazil

Synthesis of musical instruments or human voice is a time consuming process which requires theoretical and experimental knowledge about the synthesis engine. Commonly, performers need to deal with synthesizer interfaces and a process of trial and error for creating musical sounds similar to a target sound. This drawback can be overcome by adjusting automatically the synthesizer parameters using optimization algorithms. In this paper a hybrid particle swarm optimization (PSO) algorithm is proposed to solve the frequency modulation (FM) matching synthesis problem. The proposed algorithm takes advantage of a shuffle process for exchanging information between particles and applies the selective passive congregation and the opposition-based learning approaches to preserve swarm diversity. Both approaches for injecting diversity are based on simple operators, preserving the easy implementation philosophy of the particle swarm optimization. The proposed hybrid particle swarm optimization algorithm was validated for a three-nested FM synthesizer, which represents a 6-dimensional multimodal optimization problem with strong epistasis. Simulation results revealed that the proposed algorithm presented promising results in terms of quality of solutions.

关键词： Frequency modulation Optimization Equations Convergence Particle swarm optimization Genetic algorithms

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Generating multiple time series forecasts with artificial neural networks in a telecommunications company

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International Journal of industrial engineering : Theory Applications and Practice 2011年第11期18卷 591-598页

作者： Salazar-Aguilar, María A. Villarreal-Marroquín, María G. Moreno-Rodríguez, Guillermo J. Rodriguez-Sarasty, Jesus A. Cabrera-Ríos, Mauricio Graduate Program in Systems Engineering Universidad Autónoma de Nuevo León San Nicolás de los Garza Nuevo León 66450 Mexico Department of Integrated Systems Engineering Ohio State University Columbus OH 43210 United States AXTEL-México San Pedro Garza García Nuevo León 66215 Mexico Department of Industrial Engineering University of Puerto Rico Mayagüez 00681 Puerto Rico

In this work, the generation of multiple period demand forecasts was approached through the use of artificial neural networks (ANNs) for time series. The study was carried out for a telecommunications company and called for the use of a method to fine-tune the ANNs by using design of experiments (DOE) and optimization techniques. The results give evidence of better forecasting performance of the ANNs over traditional statistical techniques. © International Journal of industrial engineering.

关键词： Neural networks

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Bayesian credit scoring model with integration of expert knowledge and customer data

Bayesian credit scoring model with integration of expert kno...

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24th Mini EURO Conference on Continuous Optimization and Information-Based Technologies in the Financial Sector, MEC EurOPT 2010

作者： Biçer, Işik Seviş, Deniz Bilgiç, Taner Department of Industrial Engineering Bogaziçi University Turkey Graduate Program of Systems and Control Engineering Bogaziçi University Turkey

ISBN: (纸本)9789955285977

Bayesian classification method is one of the effective classification methods in credit scoring applications. Application of this method to credit scoring provides several advantages, which are suggested in the literature. In this research, a Bayesian credit scoring model is applied for classification of personal loan customers. The contribution of this paper is two-fold. First, we apply a Bayesian classification model to credit scoring of personal loan customers with integration of knowledge of credit experts and personal loan data. The dependency relations between the variables are constructed based on the knowledge of credit experts, and the parameters are estimated by Expectation-Maximization (EM) algorithm with real personal loan data of customers obtained from a Turkish bank. Second, we assess the effectiveness of the Bayesian credit scoring model based on additional personal loan data of the bank customers. The results show that the Bayesian credit scoring model is more effective than the logistic regression credit scoring model which has been currently used in the bank. © Izmir University of Economics, Turkey, 2010.

关键词： Sales

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The use of central composite designs to improve cytotoxicity data generation: a case study

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IIE Transactions on Healthcare systems engineering 2011年第4期1卷 226-231页

作者： Isaza, Clara E. Rodriguez, Cristina Uribe, Lyzett Perez, Hugo A. Salinas, Jannet Cabrera-Rios, Mauricio Immunology and Virology Laboratory Universidad Autonoma de Nuevo Leon San NICOLAS DE LOS GARZA Av. Universidad S/N Mexico Graduate Program in Systems Engineering Universidad Autonoma de Nuevo Leon SAN NICOLAS DE LOS GARZA Av. Universidad S/N Mexico Industrial Engineering University of Puerto Rico-Mayagüez Mayaguez 00681 PO Box 9000 Puerto Rico

Research to find new treatments for cancer generally begins with in-vitro tests to measure the toxic effect of a proposed medical treatment on cell line cultures. In general, these tests are called cytotoxicity assays. The development of experimental protocols to conduct these tests is an attractive area for the application of experimental design techniques. This work describes the improvement of an experimental protocol for the colorimetric MTT assay, one of the most common cytotoxicity tests. The MTT assay is used in this case study to characterize the cytotoxic level of a novel immunotherapy agent on the well-known HeLa cervical cancer cell line. The original protocol related cytotoxicity to treatment concentration, treatment time and initial number of cells in the test. With the application of an experimental strategy based on the central composite design, it was possible to improve the protocol to drastically reduce the consumption of reagents and the use of laboratory time while strengthening the test conclusions. © 2011 Copyright Taylor and Francis Group, LLC.

关键词： biological experiments Decision analysis design of experiments linear regression optimization

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Counting vehicles: A learning experience

Counting vehicles: A learning experience

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IIE Annual Conference and Expo 2010

作者： Cabrera-Ríos, Mauricio Maldonado Chan, Mauro J. Industrial Engineering Dept University of Puerto Rico at Mayaguez Puerto Rico Graduate Program in Systems Engineering UANL San-Nicolás-de-los-Garza N.L. Mexico

Traffic flow characterization is critical for transportation systems and urban infrastructure planning. In most major cities in Latin America, this characterization is carried out visually by a group of observers during one-hour sampling periods. Automating this process should result in higher consistency and reliability in the output statistics, as well as helping keep the people in charge of this process safe. In this project, an automatic vehicle counting and classification system prototype is presented. The system uses video images previously recorded thru a camcorder and, upon an initial setup session, proves capable of detecting, counting and classifying the passing vehicles to an acceptable error rate. The preliminary evaluation is promising and provides a solid base for the development of the complete system.

关键词： Neural networks

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Hardware particle swarm optimization based on the attractive-repulsive scheme for embedded applications

Hardware particle swarm optimization based on the attractive...

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2010 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9780769543147

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from premature convergence and high elapsed time when solving multimodal and large scale engineering problems. This problem becomes an evident drawback for embedded applications in which the microcontrollers often operates at low computational capacity. This paper proposes a hardware implementation of a parallel self-adaptive PSO algorithm based on an attractive-repulsive scheme and using the efficient floating-point arithmetic which performs computations with large dynamic range and high precision. The parallel capabilities of the PSO are exploited by implementing parallel particles directly in hardware in order to decrease the running time. In addition, the attractive-repulsive technique avoids the premature convergence problem by self-adapting the swarm behavior according to its diversity. Synthesis and simulation results for benchmark test problems were performed, demonstrating the correctness of the proposed architectures. Finally, an elapsed time comparison between the hardware and software implementations shows the suitableness of the proposed architecture for embedded applications. © 2010 IEEE.

关键词： Global optimization

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Cauchy particle swarm optimization with dynamic adaptation applied to inverse heat transfer problem

Cauchy particle swarm optimization with dynamic adaptation a...

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2010 IEEE International Conference on systems, Man and Cybernetics, SMC 2010

作者： Mariani, Viviana Cocco Neckel, Vagner Jorge Grebogi, Rafael Bartnik Dos Santos Coelho, Leandro Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil

ISBN: (纸本)9781424465880

The particle swarm optimization (PSO) algorithm is a member of the wide category of swarm intelligence methods for solving global optimization problems. Its basic idea is the simulation of simplified animal social behaviors such as fish schooling and bird flocking. PSO algorithms are attracting attentions in recent years, due to their ability of keeping good balance between convergence and diversity maintenance. Several attempts have been made to improve the performance of the original PSO algorithm. In this paper, a modified version of the original PSO based on Cauchy distribution and dynamic adaptation of inertia factor, named modified PSO (MPSO), is proposed. to estimate the unknown variables of an inverse heat transfer problem. To validate the optimization performance of the proposed MPSO, an inverse heat transfer problem is illustrated and the algorithm has to estimate its unknown variables. The results testify that the MPSO can perform well in an inverse heat transfer problem. ©2010 IEEE.

关键词： Heat transfer

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Accelerating the Shuffled Frog Leaping algorithm by parallel implementations in FPGAs

Accelerating the Shuffled Frog Leaping algorithm by parallel...

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACG University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424464388

Meta-heuristics are efficient techniques for solving large scale optimization problems in which traditional mathematical techniques are impractical or provide sub-optimal solutions. The Shuffled Frog Leaping algorithm (SFLA) is a stochastic iterative method, bio-inspired on the memetic evolution of a group of frogs when seeking for food, which combines the social behavior-based of the particle swarm optimization technique (PSO) and the global information exchange of memetic algorithms. However, the SFLA algorithm suffers on large execution times, being this problem clearly evident when solving complex optimization problems for embedded applications. This drawback can be overcome by exploiting the parallel capabilities of the SFLA. This paper proposes a hardware parallel implementation of the SFLA algorithm (HPSFLA) using FPGAs (Field programmable gate Arrays) and the efficient floating-point arithmetic. The proposed architecture allows the SFLA to improve the functionality of the algorithm as well as to decrease the execution times by implementing parallel frogs and parallel memeplexes. Three well-known benchmark problems have been used to validate the implemented algorithm and simulation results demonstrate that the HPSFLA speeds-up by factors of 362, 727 and 211 a C-code implementation using an embedded microprocessor for the Sphere, Rastrigin and Rosenbrock benchmarks problems, respectively. Synthesis, simulation and execution time results demonstrate the effectiveness of the proposed HPSFLA architecture for embedded optimization systems. © 2010 IEEE.

关键词： Global optimization

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