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Relevant bibliographies by topics / Calling sequence

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Academic literature on the topic 'Calling sequence'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Calling sequence"

1

Zhao, Zhijia, Bo Wu, Mingzhou Zhou, Yufei Ding, Jianhua Sun, Xipeng Shen, and Youfeng Wu. "Call sequence prediction through probabilistic calling automata." ACM SIGPLAN Notices 49, no. 10 (December 31, 2014): 745–62. http://dx.doi.org/10.1145/2714064.2660221.

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Chang, Chun-Tien, Chi-Neu Tsai, Chuan Yi Tang, Chun-Houh Chen, Jang-Hau Lian, Chi-Yu Hu, Chia-Lung Tsai, et al. "Mixed Sequence Reader: A Program for Analyzing DNA Sequences with Heterozygous Base Calling." Scientific World Journal 2012 (2012): 1–10. http://dx.doi.org/10.1100/2012/365104.

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The direct sequencing of PCR products generates heterozygous base-calling fluorescence chromatograms that are useful for identifying single-nucleotide polymorphisms (SNPs), insertion-deletions (indels), short tandem repeats (STRs), and paralogous genes. Indels and STRs can be easily detected using the currently available Indelligent or ShiftDetector programs, which do not search reference sequences. However, the detection of other genomic variants remains a challenge due to the lack of appropriate tools for heterozygous base-calling fluorescence chromatogram data analysis. In this study, we developed a free web-based program, Mixed Sequence Reader (MSR), which can directly analyze heterozygous base-calling fluorescence chromatogram data in .abi file format using comparisons with reference sequences. The heterozygous sequences are identified as two distinct sequences and aligned with reference sequences. Our results showed that MSR may be used to (i) physically locate indel and STR sequences and determine STR copy number by searching NCBI reference sequences; (ii) predict combinations of microsatellite patterns using the Federal Bureau of Investigation Combined DNA Index System (CODIS); (iii) determine human papilloma virus (HPV) genotypes by searching current viral databases in cases of double infections; (iv) estimate the copy number of paralogous genes, such asβ-defensin 4 (DEFB4) and its paralogHSPDP3.

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Woerner, August E., Jennifer Churchill Cihlar, Utpal Smart, and Bruce Budowle. "Numt identification and removal with RtN!" Bioinformatics 36, no. 20 (July 24, 2020): 5115–16. http://dx.doi.org/10.1093/bioinformatics/btaa642.

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Abstract Motivation Assays in mitochondrial genomics rely on accurate read mapping and variant calling. However, there are known and unknown nuclear paralogs that have fundamentally different genetic properties than that of the mitochondrial genome. Such paralogs complicate the interpretation of mitochondrial genome data and confound variant calling. Results Remove the Numts! (RtN!) was developed to categorize reads from massively parallel sequencing data not based on the expected properties and sequence identities of paralogous nuclear encoded mitochondrial sequences, but instead using sequence similarity to a large database of publicly available mitochondrial genomes. RtN! removes low-level sequencing noise and mitochondrial paralogs while not impacting variant calling, while competing methods were shown to remove true variants from mitochondrial mixtures. Availability and implementation https://github.com/Ahhgust/RtN Supplementary information Supplementary data are available at Bioinformatics online.

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O'Connell, Jared, and Jonathan Marchini. "Joint Genotype Calling With Array and Sequence Data." Genetic Epidemiology 36, no. 6 (July 20, 2012): 527–37. http://dx.doi.org/10.1002/gepi.21657.

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Tessier, Laurence, Olivier Côté, and Dorothee Bienzle. "Sequence variant analysis of RNA sequences in severe equine asthma." PeerJ 6 (October 11, 2018): e5759. http://dx.doi.org/10.7717/peerj.5759.

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Background Severe equine asthma is a chronic inflammatory disease of the lung in horses similar to low-Th2 late-onset asthma in humans. This study aimed to determine the utility of RNA-Seq to call gene sequence variants, and to identify sequence variants of potential relevance to the pathogenesis of asthma. Methods RNA-Seq data were generated from endobronchial biopsies collected from six asthmatic and seven non-asthmatic horses before and after challenge (26 samples total). Sequences were aligned to the equine genome with Spliced Transcripts Alignment to Reference software. Read preparation for sequence variant calling was performed with Picard tools and Genome Analysis Toolkit (GATK). Sequence variants were called and filtered using GATK and Ensembl Variant Effect Predictor (VEP) tools, and two RNA-Seq predicted sequence variants were investigated with both PCR and Sanger sequencing. Supplementary analysis of novel sequence variant selection with VEP was based on a score of <0.01 predicted with Sorting Intolerant from Tolerant software, missense nature, location within the protein coding sequence and presence in all asthmatic individuals. For select variants, effect on protein function was assessed with Polymorphism Phenotyping 2 and screening for non-acceptable polymorphism 2 software. Sequences were aligned and 3D protein structures predicted with Geneious software. Difference in allele frequency between the groups was assessed using a Pearson’s Chi-squared test with Yates’ continuity correction, and difference in genotype frequency was calculated using the Fisher’s exact test for count data. Results RNA-Seq variant calling and filtering correctly identified substitution variants in PACRG and RTTN. Sanger sequencing confirmed that the PACRG substitution was appropriately identified in all 26 samples while the RTTN substitution was identified correctly in 24 of 26 samples. These variants of uncertain significance had substitutions that were predicted to result in loss of function and to be non-neutral. Amino acid substitutions projected no change of hydrophobicity and isoelectric point in PACRG, and a change in both for RTTN. For PACRG, no difference in allele frequency between the two groups was detected but a higher proportion of asthmatic horses had the altered RTTN allele compared to non-asthmatic animals. Discussion RNA-Seq was sensitive and specific for calling gene sequence variants in this disease model. Even moderate coverage (<10–20 counts per million) yielded correct identification in 92% of samples, suggesting RNA-Seq may be suitable to detect sequence variants in low coverage samples. The impact of amino acid alterations in PACRG and RTTN proteins, and possible association of the sequence variants with asthma, is of uncertain significance, but their role in ciliary function may be of future interest.

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Bedo, Justin, Benjamin Goudey, Jeremy Wazny, and Zeyu Zhou. "Information theoretic alignment free variant calling." PeerJ Computer Science 2 (July 25, 2016): e71. http://dx.doi.org/10.7717/peerj-cs.71.

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While traditional methods for calling variants across whole genome sequence data rely on alignment to an appropriate reference sequence, alternative techniques are needed when a suitable reference does not exist. We present a novel alignment and assembly free variant calling method based on information theoretic principles designed to detect variants have strong statistical evidence for their ability to segregate samples in a given dataset. Our method uses the context surrounding a particular nucleotide to define variants. Given a set of reads, we model the probability of observing a given nucleotide conditioned on the surrounding prefix and suffixes of lengthkas a multinomial distribution. We then estimate which of these contexts are stable intra-sample and varying inter-sample using a statistic based on the Kullback–Leibler divergence.The utility of the variant calling method was evaluated through analysis of a pair of bacterial datasets and a mouse dataset. We found that our variants are highly informative for supervised learning tasks with performance similar to standard reference based calls and another reference free method (DiscoSNP++). Comparisons against reference based calls showed our method was able to capture very similar population structure on the bacterial dataset. The algorithm’s focus on discriminatory variants makes it suitable for many common analysis tasks for organisms that are too diverse to be mapped back to a single reference sequence.

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Mukbil, Awad, Umut Durak, and Sven Hartmann. "Conformance testing of FMI calling sequence for simulation environments." International Journal of Modeling, Simulation, and Scientific Computing 10, no. 02 (April 2019): 1950008. http://dx.doi.org/10.1142/s1793962319500089.

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Exchanging simulation models is currently of utmost importance. To improve interoperability between suppliers and original equipment manufacturers (OEMs), the functional mock-up interface (FMI) is exchanged in a standard format called functional mock-up unit (FMU). Since its first release, many simulation tools took the initiative to support FMI. However, since then, there have been many complaints stating that exchanging models via FMI does not work as stable as expected. The reason usually turned out to be the implementation of tool vendors that sometimes fail to comply with the standard fully. This paper introduces a methodology for testing FMI compliance of importing simulation tools using a set of reference FMUs. The standard defines the implementation of FMI functions calling sequence in a state machine. Therefore, conformance testing (also called fault detection) from automata theory is utilized to produce reference FMUs based on the FMI state-machine.

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Dewal, N., Y. Hu, M. L. Freedman, T. LaFramboise, and I. Pe'er. "Calling amplified haplotypes in next generation tumor sequence data." Genome Research 22, no. 2 (November 16, 2011): 362–74. http://dx.doi.org/10.1101/gr.122564.111.

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Ruark, Elise, Esty Holt, Anthony Renwick, Márton Münz, Matthew Wakeling, Sian Ellard, Shazia Mahamdallie, Shawn Yost, and Nazneen Rahman. "ICR142 Benchmarker: evaluating, optimising and benchmarking variant calling using the ICR142 NGS validation series." Wellcome Open Research 3 (August 31, 2018): 108. http://dx.doi.org/10.12688/wellcomeopenres.14754.1.

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Evaluating, optimising and benchmarking of next generation sequencing (NGS) variant calling performance are essential requirements for clinical, commercial and academic NGS pipelines. Such assessments should be performed in a consistent, transparent and reproducible fashion, using independently, orthogonally generated data. Here we present ICR142 Benchmarker, a tool to generate outputs for assessing variant calling performance using the ICR142 NGS validation series, a dataset of exome sequence data from 142 samples together with Sanger sequence data at 704 sites. ICR142 Benchmarker provides summary and detailed information on the sensitivity, specificity and false detection rates of variant callers. ICR142 Benchmarker also automatically generates a single page report highlighting key performance metrics and how performance compares to widely-used open-source tools. We used ICR142 Benchmarker with VCF files outputted by GATK, OpEx and DeepVariant to create a benchmark for variant calling performance. This evaluation revealed pipeline-specific differences and shared challenges in variant calling, for example in detecting indels in short repeating sequence motifs. We next used ICR142 Benchmarker to perform regression testing with versions 0.5.2 and 0.6.1 of DeepVariant. This showed that v0.6.1 improves variant calling performance, but there was evidence of some minor changes in indel calling behaviour that may benefit from attention in future updates. The data also allowed us to evaluate filters to optimise DeepVariant calling, and we recommend using 30 as the QUAL threshold for base substitution calls when using DeepVariant v0.6.1. Finally, we used ICR142 Benchmarker with VCF files from two commercial variant calling providers to facilitate optimisation of their in-house pipelines and to provide transparent benchmarking of their performance. ICR142 Benchmarker consistently and transparently analyses variant calling performance based on the ICR142 NGS validation series, using the standard VCF input and outputting informative metrics to enable user understanding of pipeline performance. ICR142 Benchmarker is freely available at https://github.com/RahmanTeamDevelopment/ICR142_Benchmarker/releases.

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Ruark, Elise, Esty Holt, Anthony Renwick, Márton Münz, Matthew Wakeling, Sian Ellard, Shazia Mahamdallie, Shawn Yost, and Nazneen Rahman. "ICR142 Benchmarker: evaluating, optimising and benchmarking variant calling performance using the ICR142 NGS validation series." Wellcome Open Research 3 (October 31, 2018): 108. http://dx.doi.org/10.12688/wellcomeopenres.14754.2.

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Evaluating, optimising and benchmarking of next generation sequencing (NGS) variant calling performance are essential requirements for clinical, commercial and academic NGS pipelines. Such assessments should be performed in a consistent, transparent and reproducible fashion, using independently, orthogonally generated data. Here we present ICR142 Benchmarker, a tool to generate outputs for assessing germline base substitution and indel calling performance using the ICR142 NGS validation series, a dataset of Illumina platform-based exome sequence data from 142 samples together with Sanger sequence data at 704 sites. ICR142 Benchmarker provides summary and detailed information on the sensitivity, specificity and false detection rates of variant callers. ICR142 Benchmarker also automatically generates a single page report highlighting key performance metrics and how performance compares to widely-used open-source tools. We used ICR142 Benchmarker with VCF files outputted by GATK, OpEx and DeepVariant to create a benchmark for variant calling performance. This evaluation revealed pipeline-specific differences and shared challenges in variant calling, for example in detecting indels in short repeating sequence motifs. We next used ICR142 Benchmarker to perform regression testing with DeepVariant versions 0.5.2 and 0.6.1. This showed that v0.6.1 improves variant calling performance, but there was evidence of minor changes in indel calling behaviour that may benefit from attention. The data also allowed us to evaluate filters to optimise DeepVariant calling, and we recommend using 30 as the QUAL threshold for base substitution calls when using DeepVariant v0.6.1. Finally, we used ICR142 Benchmarker with VCF files from two commercial variant calling providers to facilitate optimisation of their in-house pipelines and to provide transparent benchmarking of their performance. ICR142 Benchmarker consistently and transparently analyses variant calling performance based on the ICR142 NGS validation series, using the standard VCF input and outputting informative metrics to enable user understanding of pipeline performance. ICR142 Benchmarker is freely available at https://github.com/RahmanTeamDevelopment/ICR142_Benchmarker/releases.

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Dissertations / Theses on the topic "Calling sequence"

1

Simpson, Jared Thomas. "Efficient sequence assembly and variant calling using compressed data structures." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607828.

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Kothiyal, Prachi. "Detection and Classification of Sequence Variants for Diagnostic Evaluation of Genetic Disorders." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1275922297.

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Kutlu, Mucahid. "Parallel Processing of Large Scale Genomic Data." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1436355132.

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Shi, Xiaomeng Ph D. Massachusetts Institute of Technology. "Joint base-calling of two DNA sequences with factor graphs." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45868.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
Includes bibliographical references (p. 63-65).
The advent of DNA sequencing has revolutionized biological research by providing virtual blueprints of living organisms and offering insights into complicated biochemical processes. DNA sequencing is a process encompassing both chemical reactions and signal processing techniques to identify the order of chemical bases in a DNA molecule. In this thesis, we focus on the base-calling stage, during which base order is estimated from data collected through electrophoresis and florescence detection. In particular, we examine the possibility of jointly base-calling two superposed DNA sequences by applying the sum-product algorithm on factor graphs. This approach allows a single electrophoresis experiment to process two sequences, using the same quantity of reagents and machine hours as for a single sequence. A practical heuristic is first used to estimate the peak parameters, then separate those into two sequences (major/minor) by passing messages on a factor graph. Base-calling on the major alone yields accuracy commensurate with single sequence approaches, and joint base-calling provides results for the minor which, while being of lesser quality, incurs no additional cost and can be ultimately used in the genome assembly process.
by Xiaomeng Shi.
S.M.

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Yi-ChunLin and 林怡君. "Quality of Base Calling for NextGeneration Sequence." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/62028518932776264013.

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碩士
國立成功大學
統計學系
103
There are four different bases, adenine (A), guanine (G), cytosine (C), and thymine (T), making up DNA. Next Generation Sequencing is a new technique allowing to sequence DNA much more quickly and cheaply than the previously used Sanger sequencing. However, issue on quality of sequencing, although plays an important role in coding the DNA, does not receive much attention academically and practically. Illumina, one of the famous companies, claims that the positions of bases follow the same sequels vertically after the fourth cycle. However, several works have been conducted and proved that the positions of base calling are not fixed. See Li (2012), Shao (2013) and Lin (2014). The above authors basically used a specific region to prove that there does exist a shift in base position. In the thesis, we apply machine learning technique called eigenface recognition and principal component scores to represent the overall behavior of cycles, and find the relationship between shift and cycles using the coefficients of eigenfaces.

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Jou-AnChen and 陳柔安. "Evaluating the Quality of Base Calling for Next Generation Sequence." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/74703811397745731827.

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碩士
國立成功大學
統計學系
102
Deoxyribonucleic acid (DNA) is a molecule that encodes the genetic instructions. Each gene is composed of four bases: adenine(A), thymine(T), cytosine(C) and guanine(G). The value of assembled reads is judged by the quality of bases, which in turn by the accuracy of base calling. As a result, research about base calling becomes critical if quality of reads is to be assured. Although literatures did discuss the quality of base calling, no true sequence is available. Therefore, the accuracy of base calling can’t be obtained.In this article, we use available data from Illumina to estimate the parameters in the 4-variate distribution of true bases in every cycle, and simulate the intensity of the sequences. The best procedure of base calling we obtained include four processes:(1)deal with noise, (2)determine the threshold,(3) find candidate locations, and (4)set up the base calling criterion. In this article, we propose a method to find candidate locations of bases and suggest a better procedure in base calling.

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Chang, Chun-Tien, and 張君天. "Mixed Sequence Reader (MSR) program for analyzing DNA sequences with heterozygous base calling chromatography to detect genomic variations." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/00528151043552192902.

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博士
國立清華大學
資訊工程學系
100
When PCR products are directly sequenced, heterozygous base-calling fluorescence chromatogram data are derived for identifying single nucleotide polymorphisms (SNP), insertion-deletion (Indel), short tandem repeat (STR), and paralogous genes. Indel and STR can be easily detected using the currently available Indelligent or ShiftDetector programs without searching reference sequences. However, the detection of other genomic variants remains a challenge because of the lack of appropriate tools to analyze heterozygous base-calling fluorescence chromatogram data. In this study, we developed the free, web-based “Mixed Sequence Reader (MSR)” that can directly analyze heterozygous base-calling fluorescence chromatogram data in .abi file format with reference sequences. The heterozygous sequences can be identified as two distinct sequences and aligned with reference sequences. Our results showed that MSR may be used for: (i) physically locating Indel and STR sequences by searching the NCBI reference sequences, and determining the copy number of STR, (ii) predicting the combinations of microsatellite pattern using Federal Bureau of Investigation Combined DNA Index System (CODIS), (iii) determining human papilloma virus (HPV) genotypes by searching current viral databases in cases of multiple infections, and (iv) estimating the copy number of paralogous genes, such as β-defensin 4, DEFB4, and its paralog HSPDP3

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Books on the topic "Calling sequence"

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Levin, Tomer T., and Alison Wiesenthal. Talking about dying. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198736134.003.0022.

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Talking intimately about a person’s death is a poignant conversation. The intensity of this is reduced by locating the discussion within a review of the goals of care and inviting consideration of natural forms of dying. A sequence of well-rehearsed strategies informed by patient-centredness and compassionate support serves the effective accomplishment of this task. Family support is an important related task, often calling for a family meeting to optimize outcomes. Withdrawal of life-prolonging therapies, handling requests for hastened death or futile care, and responding to misunderstanding and family conflict are common predicaments. The use of educational videos about end-of-life decision-making has improved understanding. Clinicians need to be able to comfortably discuss any potential mode of dying and assure the patient and their family of their continuing and committed care. Communication skills training with simulated patients helps optimize the ease with which clinicians can talk about death and dying.

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Book chapters on the topic "Calling sequence"

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Rimmer, Andy. "Calling Variants from Sequence Data." In Assessing Rare Variation in Complex Traits, 15–31. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2824-8_2.

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Hansen, Nancy F. "Variant Calling From Next Generation Sequence Data." In Methods in Molecular Biology, 209–24. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3578-9_11.

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Bernhardsson, Carolina, Xi Wang, Helena Eklöf, and Pär K. Ingvarsson. "Variant Calling Using Whole Genome Resequencing and Sequence Capture for Population and Evolutionary Genomic Inferences in Norway Spruce (Picea Abies)." In Compendium of Plant Genomes, 9–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-21001-4_2.

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Metcalfe, David, and Harveer Dev. "Effective Communication." In Oxford Assess and Progress: Situational Judgement Test. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805809.003.0022.

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Communication is fundamental to the role of the doctor. It includes routine verbal communication (e.g. history taking, updating relatives, handovers, and requesting investigations from specialists), written communication (e.g. prescriptions, updating the clinical notes, and discharge summaries), breaking bad news, and ‘challenging’ interactions such as dealing with an angry relative. Questions within this section assess your ability to communicate effectively with patients and colleagues. Effective communication requires understanding and being understood. You will need to demonstrate an ability to negotiate with colleagues, to document information within the medical notes clearly and concisely, to gather information from patients, and to listen to angry relatives. As always, your responses must adapt to the needs and context of each situation, while always remembering to demonstrate empathy and compassion. ● Listen to patients, relatives, and colleagues. They are trying to tell you something. ● Explain your position carefully after listening to the other side. ● Adapt your style as far as possible to the person with whom you are communicating. ● However strongly you feel, poor manners will never get the job done faster. Foundation doctors should not usually be left to ‘break bad news’ in the classical sense of a new cancer diagnosis in clinic. However, bad news can take many forms and it is likely that you will find yourself going through the ‘breaking bad news’ sequence many times during the foundation programme. For example, the following scenarios are all bad news to varying degrees. Some patients will take such developments in their stride and others will rank them amongst other significant life events. ● An incidental ‘nodule’ found on a CT chest that might be benign but will require a follow- up scan in three months. ● An elderly man who has become very unwell and is unlikely to survive while you are on call. You have been assigned the task of calling his wife, providing an update, and suggesting she come to the hospital urgently. ● The fact that investigations have all been normal and they are being discharged without a diagnosis for their persistent debilitating abdominal pain.

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Conference papers on the topic "Calling sequence"

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Simon. "Assignment and sequence." In the 11th Koli Calling International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2094131.2094134.

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Zhao, Zhijia, Bo Wu, Mingzhou Zhou, Yufei Ding, Jianhua Sun, Xipeng Shen, and Youfeng Wu. "Call sequence prediction through probabilistic calling automata." In SPLASH '14: Conference on Systems, Programming, and Applications: Software for Humanity. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2660193.2660221.

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Glumac, Slaven, and Zdenko Kovacic. "Calling Sequence Calculation for Sequential Co-simulation Master." In SIGSIM-PADS '18: SIGSIM Principles of Advanced Discrete Simulation. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3200921.3200924.

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Beal, Christopher R., John G. Peters, and Ronald J. Nowling. "Sequence model evaluation framework for STARR-seq peak calling." In BCB '21: 12th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3459930.3469488.

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Ye, Lu, and JingYang Gao. "Integrated Sequence Assembly-based Approach for Calling Genomic Long Insertion." In 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/amcce-17.2017.147.

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Bailey, Mark W., and Jack W. Davidson. "Target-sensitive construction of diagnostic programs for procedure calling sequence generators." In the ACM SIGPLAN 1996 conference. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/231379.231431.

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Zhang, Jinfang, Bo Yuan, Xiaochen Wang, and Nan Li. "Research on calling sequence of peaking regulation means in power system with pumped hydro power (PHP) station." In 2017 2nd International Conference on Power and Renewable Energy (ICPRE). IEEE, 2017. http://dx.doi.org/10.1109/icpre.2017.8390594.

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Howell, Steve, Tim Harrington, Debra Larson, Ken Collier, and Jerry Hatfield. "A Virtual Corporation: An Interdisciplinary and Collaborative Undergraduate Design Experience." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dfm-1267.

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Abstract Engineering industries are calling for graduates that have a breadth of skills including design and analysis skills, teaming skills and “soft skills” (i.e., project management, concept value analysis, communication, cross-disciplinary understanding, etc.) Furthermore, many American industries are implementing “virtual project work teams”, where expert teams work concurrently in several remote locations, sharing design information and data electronically. Northern Arizona University’s College of Engineering and Technology is implementing an innovative, four-year, sequence of classes called the Path to Synthesis. The sophomore and junior courses in the Path to Synthesis program are team-taught industry simulations which use collaborative product design to not only develop design skills, teamwork skills, and soft engineering skills, but to also encourage the use of state of the art design methods and professional software tools. During the Fall 1995 semester, a “virtual team” paradigm was introduced into these two classes. NAU students worked with “expert” teams at other institutions to collaboratively complete a major design project. Students used modern high speed electronic media to communicate design ideas, share electronic data, and complete a project which required expertise from student teams dispersed across a wide geographic area. This paper describes the piloted junior and sophomore level Path to Synthesis courses, and how geographically distributed teams located in Flagstaff, Tempe, and San Francisco collaborated on different aspects of an industrial simulation. This collaborative effort required the use of modern high speed electronic networks for communication, live two way video interaction, and transfer of graphic and CAD data.

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Pe´rez Rodri´guez, Norberto, Erik Rosado Tamariz, and Rafael Garci´a Illescas. "Supervision During Commissioning Procedure for Commercial Operation of 32 MW Turbogas Power Plants." In ASME 2008 Power Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/power2008-60025.

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This article presents the supervision and testifying process during the start of commercial operations of several turbogas plants generating electricity rate of 32 MW each fuelled by natural gas. Supervision and testifying process were conducted at the request of the customer to confirm and observe that the evidence of commissioning, testing and operation of acceptance tests were carried out as specified by international regulations, calling the outcome of each tests agree the applied rules. The work was done in collaboration with the supplier and manufacturer of equipment, the client and the institution responsible for certification and approval of the plant. All this according to a logical and chronological order for the sequence of tests commissioning, operation and acceptance. Tests for putting into service are carried out on-site at normal operating conditions, according to the design and operation needs of the plant. Once implemented in full and in a satisfactory manner, test operation of each plant was carried out considering that they must operate automatically, reliable, stable and secure, fulfilling at least, one hundred hours of operation at full load. After completed operation tests are conducted, acceptance testing on the power plant and integrated approach to assessing the quality of the product were accomplished. Finally, it was verified if each unit meets the technical requirements established in terms of thermal capacity of the machine, noise levels and emissions. As a result of this supervision and testifying process, it is guaranteed to the client that the power plants and all their equipment, comply with the requirements, conditions and specifications in agreement with the supplier, concerning test of putting into service, operational and acceptance tests.

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Xiaomeng Shi, Desmond S. Lun, Jim Meldrim, Ralf Kotter, and Muriel Medard. "Joint base-calling of two DNA sequences with factor graphs." In ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4518043.

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