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Pawel Wojciechowski, Wojciech Frohmberg, Michal Kierzynka, Piotr Zurkowski and Jacek Blazewicz

nucleotide reads, Bulletin of the Polish Academy of Sciences Technical Sciences , 61 , 4, 2013, 989–992. [7] Holtgrewe, M., Mason – a read simulator for second generation sequencing data, Technical Report Institut für Mathematik und Informatik, Freie Universität Berlin , TR-B-10-06, 2010. [8] Holtgrewe, M., Emde, A.-K., Weese, D., Reinert, K., A Novel And Well-Defined Benchmarking Method For Second Generation Read Mapping BMC Bioinformatics , 12 , 210, 2011. [9] Kierzynka, M., GPU-accelerated graph construction for the whole genome assembly, Phd

Open access

Alexandros Mittos, Bradley Malin and Emiliano De Cristofaro

References [ABOS15] M. Akgün, A. O. Bayrak, B. Ozer, and M. Ş. Sağgıroğglu. Privacy Preserving Processing of Genomic Data: A Survey. Journal of Biomedical Informatics , 56:103–111, 2015. [ADHT15] E. Ayday, E. De Cristofaro, J.-P. Hubaux, and G. Tsudik. The Chills and Thrills of Whole Genome Sequencing. IEEE Computer , 2015. [AKSX04] R. Agrawal, J. Kiernan, R. Srikant, and Y. Xu. Order Preserving Encryption for Numeric Data. In ACM SIGMOD , pages 563–574, 2004. [AMH + 16] A. Aziz, M. Momin, M. Z. Hasan, N. Mohammed, and D. Alhadidi

Open access

Dominic Deuber, Christoph Egger, Katharina Fech, Giulio Malavolta, Dominique Schröder, Sri Aravinda Krishnan Thyagarajan, Florian Battke and Claudia Durand

References [1] Breast cancer risk factors - genetics. http://www.breastcancer.org/risk/factors/genetics . [2] Python cryptography toolkit (pycrypto). https://pypi.python.org/pypi/pycrypto . Accessed: 2017-05-18. [3] Research – 23andme. https://www.23andme.com/enint/research/ . [Online; accessed 28-May-2018]. [4] Researchkit. http://researchkit.org/ . [Online; accessed 28-May-2018]. [5] Initial sequencing and analysis of the human genome. Nature , 409(6822):860–921, 02 2001. [6] Gail-Joon Ahn, Moti Yung, and Ninghui Li

Open access

Péter Fehér, Ágnes Fülöp, Gergely Debreczeni, Máté Nagy-Egri and György Vesztergombi

58 (2006) 80–83. ⇒173 [7] B. Langmead, C. Trapnell, M. Pop, Sl. Salzberg, Ultrafast and memory-efficient alignment of short DNA sequences to the human genome Genome Biol. 10:R25., ⇒152 [8] E. Lederberg, Lysogenicity in Eescherichia coli strain K-12, Microbial Genetics Bulletin , 1 (1950) 5–8. ⇒182 [9] J. von Neumann, First Draft of a Report on the EDVAC pp. 149. University of Pennsylvania, June 30. 1945. ⇒165 [10] T. F. Smith, M. S. Waterman, Identification of common molecular subsequences, Journal of Molecular Biology 147 (1981

Open access

Andrzej Tomski, Marcin Piechota and Ryszard Przewłocki

Abstract

Modern high-throughput sequencing techniques generate a constantly increasing amount of genomic data from eukaryotes. The main problem is quickly identifying the data that may provide information about the nature of intracellular processes, such as the targeting of transcription factor-binding sites. Typically, thousands of peaks or signals are found across the genome and the nearby genes must be annotated. We introduce AnnoGene - a web service for annotating genomic features. AnnoGene was implemented in a representational state transfer (REST) architectural style. The program searches for the gene nearest to the center of a genomic position. Subsequently, the location and annotationsof the gene are shown. The tool can be downloaded and run on a local computer, but it was designed to be a web service. AnnoGene is freely available through a web browser. Moreover, our paper covers examples of the REST clients written in the Python, R and Java programming languages. AnnoGene only requires genomic positions from the user. Even when annotating several thousand positions, the output is typically ready in a few seconds. Moreover, this tool supports Seqinspector – a web tool for finding regulators of the genes.

Open access

Dean Palejev

References 1. Anders, S., W. Huber. Differential Expression Analysis for Sequence Count Data. - Genome Biology, Vol. 11, 2010, R106. https://doi.org/10.1186/gb-2010-11-10-r106 2. Love, M. I., W. Huber, S. Anders. Moderated Estimation of Fold Change and Dispersion for RNA-seq Data with DESeq2. - Genome Biology, Vol. 12, 2014, No 12, 550. https://doi.org/10.1186/s13059-014-0550-8 3. Robinson, M. D., D. J. Mccarthy, G. K. Smyth. EdgeR: A Bioconductor Package for Differential Expression Analysis of Digital Gene

Open access

Natalia Novoselova, Igor Tom, Arkady Borisov and Inese Polaka

, and M.A. Hall, “Gene selection from microarray data for cancer classification a machine learning approach”, in Comp Biol Chem., vol. 29, 2005, pp. 37-46. [5] R. Kohavi and G. John, “Wrapper for feature subset selection”, in Artificial Intelligence, vol. 97, no. 1, 1997, pp. 273-324. [6] J.G. Thomas, J.M. Olson, S.J. Tapscott, and L.P. Zhao, “An efficient and robust statistical modeling approach to discover differentially expressed genes using genomic expression profiles”, in Genome Res., vol. 11, 2001, pp. 1227

Open access

Daniel Eth, Juan-Carlos Foust and Brandon Whale

Tripp, S. and Grueber, M. 2011. Economic Impact of the Human Genome Project. Battelle Memorial Institute. Available electronically at http://battelle.org/docs/default-documentlibrary/economic_impact_of_the_human_genome_project.pdf 2045 Initiative. 2013. 2045 Initiative. Available electronically at http://2045.com

Open access

Shouguo Tang, Yong Li and Zhikun Zhang

Algorithm for Parameter Estimation of the 2-Chlorophenol Oxidation in Supercritical Water. - Applied Mathematical Modeling, Vol. 01.37, 2013, No 3, pp. 1137-1146. 20. Lobry, J. R., N. Sueoka. Asymmetric Directional Mutation Pressures in Bacteria. - Genome Biology, Vol. 3, 2002, No 10, pp. 00-14. 21. Shah, K., A. Krishnamachari. Nucleotide Correlation Based Measure for Identifying Origin of Replication in Genomic Sequences. - BioSystems, Vol. 107, 2012, No 1, pp. 52-55. 22. Schneider, T. D. A Brief Review of Molecular

Open access

Jacek Blazewicz, Wojciech Frohmberg, Piotr Gawron, Marta Kasprzak, Michal Kierzynka, Aleksandra Swiercz and Pawel Wojciechowski

References [1] J. Bang-Jensen and G. Gutin, Digraphs. Theory, Algorithms and Applications, Springer-Verlag (2007). [2] J. Blazewicz, M. Bryja, M. Figlerowicz, P. Gawron, M. Kasprzak, E. Kirton, D. Platt, J. Przybytek, A. Swiercz, and L. Szajkowski, Whole genome assembly from 454 sequencing output via modied DNA graph concept, Computational Biology and Chemistry 33 (2009) 224{230. [3] J. Blazewicz, P. Formanowicz, M. Kasprzak, W.T. Markiewicz, and A. Swiercz, Tabu search algorithm for DNA sequencing by