Relevant bibliographies by topics / Short Read Mapping (SRM)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Short Read Mapping (SRM)'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Short Read Mapping (SRM)"

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Chon, Alvin, and Xiaoqiu Huang. "SRAMM: Short Read Alignment Mapping Metrics." International Journal on Bioinformatics & Biosciences 11, no. 02 (June 30, 2021): 01–07. http://dx.doi.org/10.5121/ijbb.2021.11201.

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Short Read Alignment Mapping Metrics (SRAMM): is an efficient and versatile command line tool providing additional short read mapping metrics, filtering, and graphs. Short read aligners report MAPing Quality (MAPQ), but these methods generally are neither standardized nor well described in literature or software manuals. Additionally, third party mapping quality programs are typically computationally intensive or designed for specific applications. SRAMM efficiently generates multiple different concept-based mapping scores to provide for an informative post alignment examination and filtering process of aligned short reads for various downstream applications. SRAMM is compatible with Python 2.6+ and Python 3.6+ on all operating systems. It works with any short read aligner that generates SAM/BAM/CRAM file outputs and reports 'AS' tags. It is freely available under the MIT license at http://github.com/achon/sramm.
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Cline, Eliot, Nuttachat Wisittipanit, Tossapon Boongoen, Ekachai Chukeatirote, Darush Struss, and Anant Eungwanichayapant. "Recalibration of mapping quality scores in Illumina short-read alignments improves SNP detection results in low-coverage sequencing data." PeerJ 8 (December 7, 2020): e10501. http://dx.doi.org/10.7717/peerj.10501.

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Background Low-coverage sequencing is a cost-effective way to obtain reads spanning an entire genome. However, read depth at each locus is low, making sequencing error difficult to separate from actual variation. Prior to variant calling, sequencer reads are aligned to a reference genome, with alignments stored in Sequence Alignment/Map (SAM) files. Each alignment has a mapping quality (MAPQ) score indicating the probability a read is incorrectly aligned. This study investigated the recalibration of probability estimates used to compute MAPQ scores for improving variant calling performance in single-sample, low-coverage settings. Materials and Methods Simulated tomato, hot pepper and rice genomes were implanted with known variants. From these, simulated paired-end reads were generated at low coverage and aligned to the original reference genomes. Features extracted from the SAM formatted alignment files for tomato were used to train machine learning models to detect incorrectly aligned reads and output estimates of the probability of misalignment for each read in all three data sets. MAPQ scores were then re-computed from these estimates. Next, the SAM files were updated with new MAPQ scores. Finally, Variant calling was performed on the original and recalibrated alignments and the results compared. Results Incorrectly aligned reads comprised only 0.16% of the reads in the training set. This severe class imbalance required special consideration for model training. The F1 score for detecting misaligned reads ranged from 0.76 to 0.82. The best performing model was used to compute new MAPQ scores. Single Nucleotide Polymorphism (SNP) detection was improved after mapping score recalibration. In rice, recall for called SNPs increased by 5.2%, while for tomato and pepper it increased by 3.1% and 1.5%, respectively. For all three data sets the precision of SNP calls ranged from 0.91 to 0.95, and was largely unchanged both before and after mapping score recalibration. Conclusion Recalibrating MAPQ scores delivers modest improvements in single-sample variant calling results. Some variant callers operate on multiple samples simultaneously. They exploit every sample’s reads to compensate for the low read-depth of individual samples. This improves polymorphism detection and genotype inference. It may be that small improvements in single-sample settings translate to larger gains in a multi-sample experiment. A study to investigate this is ongoing.
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Yang, Xiaohong, Yue Li, Yu Wei, Zhanlong Chen, and Peng Xie. "Water Body Extraction from Sentinel-3 Image with Multiscale Spatiotemporal Super-Resolution Mapping." Water 12, no. 9 (September 17, 2020): 2605. http://dx.doi.org/10.3390/w12092605.

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Water body mapping is significant for water resource management. In the view of 21 spectral bands and a short revisit time of no more than two days, a Sentinel-3 OLCI (Ocean and Land Colour Instrument) image could be the optimum data source in the near-real-time mapping of water bodies. However, the image is often limited by its low spatial resolution in practice. Super-resolution mapping (SRM) is a good solution to generate finer spatial resolution maps than the input data allows. In this paper, a multiscale spatiotemporal super-resolution mapping (MSST_SRM) method for water bodies is proposed, particularly for Sentinel-3 OLCI images. The proposed MSST_SRM method employs the integrated Normalized Difference Water Index (NDWI) images calculated from four near-infrared (NIR) bands and Green Band 6 of the Sentinel-3 OLCI image as input data and combined the spectral, multispatial, and temporal terms into one objective function to generate a fine water body map. Two experiments in the Tibet Plate and Daye lakes were employed to test the effectiveness of the MSST_SRM method. Results revealed that by using multiscale spatial dependence under the framework of spatiotemporal super-resolution Mapping, MSST_SRM could generate finer water body maps than the hard classification method and the other three SRM-based methods. Therefore, the proposed MSST_SRM method shows marked efficiency and potential in water body mapping using Sentinel-3 OLCI images.
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Canzar, Stefan, and Steven L. Salzberg. "Short Read Mapping: An Algorithmic Tour." Proceedings of the IEEE 105, no. 3 (March 2017): 436–58. http://dx.doi.org/10.1109/jproc.2015.2455551.

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Deorowicz, Sebastian, and Adam Gudyś. "Whisper 2: Indel-sensitive short read mapping." SoftwareX 14 (June 2021): 100692. http://dx.doi.org/10.1016/j.softx.2021.100692.

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David, Matei, Misko Dzamba, Dan Lister, Lucian Ilie, and Michael Brudno. "SHRiMP2: Sensitive yet Practical Short Read Mapping." Bioinformatics 27, no. 7 (January 28, 2011): 1011–12. http://dx.doi.org/10.1093/bioinformatics/btr046.

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Smith, A. D., W. Y. Chung, E. Hodges, J. Kendall, G. Hannon, J. Hicks, Z. Xuan, and M. Q. Zhang. "Updates to the RMAP short-read mapping software." Bioinformatics 25, no. 21 (September 7, 2009): 2841–42. http://dx.doi.org/10.1093/bioinformatics/btp533.

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Gao, Lei, Cong Wu, and Lin Liu. "AUSPP: A universal short-read pre-processing package." Journal of Bioinformatics and Computational Biology 17, no. 06 (December 2019): 1950037. http://dx.doi.org/10.1142/s0219720019500379.

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There are many short-read aligners that can map short reads to a reference genome/sequence, and most of them can directly accept a FASTQ file as the input query file. However, the raw data usually need to be pre-processed. Few software programs specialize in pre-processing raw data generated by a variety of next-generation sequencing (NGS) technologies. Here, we present AUSPP, a Perl script-based pipeline for pre-processing and automatic mapping of NGS short reads. This pipeline encompasses quality control, adaptor trimming, collapsing of reads, structural RNA removal, length selection, read mapping, and normalized wiggle file creation. It facilitates the processing from raw data to genome mapping and is therefore a powerful tool for the steps before meta-analysis. Most importantly, since AUSPP has default processing pipeline settings for many types of NGS data, most of the time, users will simply need to provide the raw data and genome. AUSPP is portable and easy to install, and the source codes are freely available at https://github.com/highlei/AUSPP .
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Hach, Faraz, Fereydoun Hormozdiari, Can Alkan, Farhad Hormozdiari, Inanc Birol, Evan E. Eichler, and S. Cenk Sahinalp. "mrsFAST: a cache-oblivious algorithm for short-read mapping." Nature Methods 7, no. 8 (August 2010): 576–77. http://dx.doi.org/10.1038/nmeth0810-576.

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Martinez, Hector, Joaquin Tarraga, Ignacio Medina, Sergio Barrachina, Maribel Castillo, Joaquin Dopazo, and Enrique S. Quintana-Orti. "Concurrent and Accurate Short Read Mapping on Multicore Processors." IEEE/ACM Transactions on Computational Biology and Bioinformatics 12, no. 5 (September 1, 2015): 995–1007. http://dx.doi.org/10.1109/tcbb.2015.2392077.

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Dissertations / Theses on the topic "Short Read Mapping (SRM)"

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Porter, Jacob Stuart. "Mapping Bisulfite-Treated Short DNA Reads." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/82870.

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Epigenetics are stable heritable traits that are not a result of the DNA sequence. Epigenetic modification of DNA cytosine plays a role in development and disease. The covalent bonding of a methyl group or a hydroxymethyl group to the 5-carbon of cytosine epigenetically modifies cytosine to 5-methylcytosine or 5-hydroxymethylcytosine. Upon PCR amplification, the bisulfite treatment of DNA converts unmethylated cytosine to thymine, while 5-methylcytosine, 5-hydroxymethylcytosine, and other bases remain unchanged. The resulting sequences can be mapped to a reference genome; however, this can be challenging due to sequencing technology complexity, low sequence complexity, and biases and errors introduced with bisulfite treatment. Once the short read is mapped, the identity of 5-methylcytosine or 5-hydroxymethylcytosine can be determined by comparing the mapped read to the aligned reference genome. Bisulfite DNA read mapping is characterized by mapping performance as low as 40%. This research improves bisulfite short read mapping quality. First, reads generated from the bisulfite hairpin PCR protocol are used to study mapping failure and solutions. A read may not map to the genome; it may map uniquely, or it may map to multiple locations. Sequence complexity correlates with these mapping categories. The hairpin protocol allows for a recovery, in some cases, of the original untreated read, and mapping this read with the regular read mapper Bowtie2 improved mapper performance by 10%. New bisulfite read mapping software called BisPin was created that calls BFAST (BLAT-like Fast Accurate Search Tool) for mapping. BisPin resolves ambiguously mapped reads with a rescoring strategy, which yields a statistically significant improvement. BFAST-Gap for Ion Torrent reads was developed, since Ion Torrent machines are less expensive than Illumina machines and since Ion Torrent reads are longer. There are few mappers for Ion Torrent data. BFAST-Gap uses homopolymer run length for contextual gap penalty functions, since homopolymer runs cause errors in Ion Torrent reads. In conjunction with BisPin, this software performed well on real and simulated bisulfite Ion Torrent data and Illumina data. InfoTrim, a read trimmer with an entropy term, was developed with competitive results.
Ph. D.
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Chacon, de San Baldomero Alejandro. "Read mapping on heterogeneous systems: scalability strategies for bioinformatic primitives." Doctoral thesis, Universitat Autònoma de Barcelona, 2021. http://hdl.handle.net/10803/671736.

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La seqüenciació genòmica és un component clau en nous avenços en medicina, i la seva democratització és un pas important per millorar l’accessibilitat per al pacient. Els beneficis implícits en el descobriment de noves variants genètiques són molt amplis, incloent des de la detecció precoç de càncer com la medicina personalitzada, passant pel disseny de fàrmacs i l’edició genòmica. Tots aquests usos potencials han incrementat exponencialment l’interès de la comunitat científica en el camp de la bioinformàtica durant els últims anys. A més, el sorgiment dels mètodes de Seqüenciació de Nova Generació ha contribuït a la reducció ràpida dels costos de seqüenciació, permetent el desenvolupament de noves aplicacions genòmiques. El principal objectiu d’aquesta tesi és el de millorar el rendiment i precisió de l’estat de l’art de la seqüenciació genètica a través de l’ús de plataformes de còmput heterogeni i sistemes de computació híbrida. Més específicament, el treball s’ha centrat en l’acceleració de el problema de mapeig de reads curts, ja que es descriu com un dels estadis del pipeline amb un major cost computacional. De forma global, s’ aspirava a reduir el temps de processament i el cost de la seqüenciació genètica, incrementant la disponibilitat d’aquest tipus d’anàlisi. La principal contribució d’aquesta tesi és la integració GPU del mapper GEM3 (GEM3-GPU). Aquest mapper reporta les mateixes dades de sortida per CPU i GPU, i és un dels primers mappers GPU que permet l’alineament de reads llargs i variables. Les propostes han estat validades utilitzant dades reals, ja que el mapper ha estat corrent en producció en un centre de seqüenciació genòmica (Centre Nacional d’Anàlisi Genòmica (CNAG)). En conjunció amb el mapper GEM3-GPU, durant aquesta tesi s’ha creat una llibreria bioinformàtica en CUDA (GEM-cutter). La llibreria aporta blocs de primitives GPU bàsiques que han estat altament optimitzades. Gem-cutter ofereix una API basada en primitives send and receive (message passing), i incorpora un scheduler per balancejar el treball. A més, la llibreria suporta totes les arquitectures GPU i Multi-GPU.
La secuenciación genómica es un componente clave en nuevos avances en medicina, y su democratización es un paso importante hacia la accesibilidad para el paciente. Los beneficios implícitos en el descubrimiento de nuevas variantes genéticas son muy amplios, incluyendo desde la detección precoz de cáncer como la medicina personalizada, pasando por el diseño de fármaco y la edición genómica. Estos usos potenciales han incrementado exponencialmente el interés de la comunidad científica en el campo de la bioinformática durante los últimos años. Además, el surgimiento de los métodos de Secuenciación de Nueva Generación ha contribuido a la reducción rápida de los costes de secuenciación, permitiendo el desarrollo de nuevas aplicaciones genómicas. El principal objetivo de esta tesis es el de mejorar el rendimiento y precisión del estado del arte de la secuenciación genética a través del uso de plataformas de computo heterogéneo y sistemas de hardware híbridos. Más específicamente, el trabajo se ha centrado en la aceleración del problema del short-read mapping, dado que se describe como uno de los estadíos del pipeline con un mayor coste computacional. De forma global, se aspiraba a reducir el tiempo de procesado y el coste de la secuenciación genética, incrementando su disponibilidad. La principal contribución de esta tesis es la integración GPU del mapper GEM3 (GEM3-GPU). Este mapper reporta los mismos datos de salida para CPU y GPU, y es uno de los primeros mappers GPU que permite el alineamiento de reads largos y variables. Las propuestas han sido validadas utilizando datos reales, dado que el mapper ha estado corriendo en producción en un centro de secuenciación (Centro Nacional de Análisis Genómico (CNAG)). En conjunción con el mapper GEM3-GPU, durante esta tesis se ha creado una librería bioinformática en CUDA (GEM-cutter). La librería provee bloques de primitivas GPU básicas que han sido altamente optimizadas. Gem-cutter ofrece una API basada en primitivas de send and receive (message passing), e incorpora un scheduler para balancear el trabajo. Además, la librería soporta todas las arquitecturas GPU y Multi-GPU.
Genomic sequencing is the key component of new advances in medicine, and its democratization is an important step in improving accessibility for the patient. The benefits involved in discovering new genomic variations are vast and include everything from early cancer detection to personalized medicine, drug design and genome editing. All of these potential uses have greatly increased the interest of the scientific community in the field of bioinformatics in recent years. Moreover, the emergence of next-generation sequencing methods has contributed to the rapid reduction of sequencing costs, enabling new applications of genomics in precision medicine. The main goal of this thesis is to improve the state of the art in performance and accuracy for genome sequencing through the use of heterogeneous computing platforms and hybrid hardware systems. More specifically, the work is focused on accelerating the problem of short-read mapping, as it is described as one of the most computationally expensive parts of the pipeline process. Overall, we aim to reduce the processing time and cost of genome sequencing, and then increasing the availability of this type analysis. The main contribution of this thesis is the full GPU integration of the GEM3 mapper (GEM3-GPU), reporting significant improvements in performance and competitive accuracy results. The mapper reports the same output files for CPU and GPU and is one of the first GPU mappers to allow very long and variable read alignment. The proposals have been validated using real data, since the mapper has been running in production at a genomic sequencing center (Centro Nacional de Análisis Genómico (CNAG)). Together with the GEM3-GPU mapper, a complete bioinformatics CUDA library (GEM-cutter) has been created. The library provides the basic building blocks for genomic applications, which are highly optimised to run on GPUs. Gem-cutter offers an API based on send and receive primitives (message passing) and incorporates a scheduler to balance the work. Furthermore, the library supports all GPU architectures and Multi-GPU execution.
Universitat Autònoma de Barcelona. Programa de Doctorat en Informàtica
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Book chapters on the topic "Short Read Mapping (SRM)"

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Ribeca, Paolo. "Short-Read Mapping." In Bioinformatics for High Throughput Sequencing, 107–25. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_7.

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Zhou, Xueya, Suying Bao, Binbin Wang, Xuegong Zhang, and You-Qiang Song. "Short Read Mapping for Exome Sequencing." In Methods in Molecular Biology, 93–111. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-514-9_6.

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Menzel, Peter, Jes Frellsen, Mireya Plass, Simon H. Rasmussen, and Anders Krogh. "On the Accuracy of Short Read Mapping." In Methods in Molecular Biology, 39–59. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-514-9_3.

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Morshedi, Mostafa, and Hamid Noori. "FPGA Implementation of a Short Read Mapping Accelerator." In Lecture Notes in Computer Science, 289–96. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56258-2_25.

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Mäkinen, Veli, Niko Välimäki, Antti Laaksonen, and Riku Katainen. "Unified View of Backward Backtracking in Short Read Mapping." In Algorithms and Applications, 182–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12476-1_13.

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Kimura, Kouichi, Asako Koike, and Kenta Nakai. "Seed-Set Construction by Equi-entropy Partitioning for Efficient and Sensitive Short-Read Mapping." In Lecture Notes in Computer Science, 151–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23038-7_14.

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Bhatia, Dinesh, and Animesh Mishra. "A Novel Artificial Intelligence Technique for Analysis of Real-Time Electro-Cardiogram Signal for the Prediction of Early Cardiac Ailment Onset." In Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering, 42–66. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2120-5.ch003.

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The role of ECG analysis in the diagnosis of cardio-vascular ailments has been significant in recent times. Although effective, the present computational algorithms lack accuracy, and no technique till date is capable of predicting the onset of a CVD condition with precision. In this chapter, the authors attempt to formulate a novel mapping technique based on feature extraction using fractional Fourier transform (FrFT) and map generation using self-organizing maps (SOM). FrFT feature extraction from the ECG data has been performed in a manner reminiscent of short time Fourier transform (STFT). Results show capability to generate maps from the isolated ECG wavetrains with better prediction capability to ascertain the onset of CVDs, which is not possible using conventional algorithms. Promising results provide the ability to visualize the data in a time evolution manner with the help of maps and histograms to predict onset of different CVD conditions and the ability to generate the required output with unsupervised training helping in greater generalization than previous reported techniques.
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Fox, Heather A. "Mapping Spatial Consciousness in Kate Chopin’S Bayou Folk (1894)." In Arranging Stories, 19–56. University Press of Mississippi, 2022. http://dx.doi.org/10.14325/mississippi/9781496840516.003.0002.

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This chapter traces the textual history of four stories—“Beyond the Bayou,” “The Return of Alcibiade,” “A Wizard from Gettysburg,” and “Ma’ame Pélagie”—from their initial publications in periodicals to their inclusion in Kate Chopin’s first short story collection, Bayou Folk (1894). These stories portray the aftermath of the Civil War in Louisiana between the 1860s and 1890s. When read together, they demonstrate a progressively deteriorating landscape, strategically revising northern magazine editors’ positioning of the South as sentimental and exotic to magnify the social concerns that continued to envelope a nation recovering from war. It demonstrates how Chopin challenges geographic boundaries through her narrative representations of them to develop a reader’s spatial consciousness about relationships between dominant power structures and regional exceptionalism.
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J. Espona, Maria. "Interdisciplinary Integrated Tools to Problem Solving 2.0." In Contemporary Issues in Information Systems - A Global Perspective. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101456.

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Everyone understands the events they witness or read about according to their mental models, and that is one of the main reasons there are a lot of disagreements at workplaces and between friends and families. Considering this situation, plus the difficulty that most people face when trying to conceptualize problems, I suggest a course that includes series methodologies, working synergistically to deal with this problem that goes from understanding the differences between people to test multiple hypotheses and planning the solution implementation. Since 2014, I have been teaching with some colleagues this tool in the format of a short course that articulates systems thinking, mapping studies, information quality, and competing hypotheses. This course has been presented often not only in Argentina and also in Peru with great success. Considering the pandemic situation, since 2020, it has been taught virtually. The latest modification to the original structure of the course was the incorporation of the Gantt chart to design the implementation of the solution found. This paper will present our course and the logic behind it, its outcomes, and how it evolved with the different iterations.
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Fiore, Teresa. "All at One Point: The Unlikely Connections between Italy’s Emigration, Immigration, and (Post)Colonialism." In Pre-Occupied Spaces. Fordham University Press, 2017. http://dx.doi.org/10.5422/fordham/9780823274321.003.0001.

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The introduction opens with a reading of Italo Calvino’s poignant short story “All at One Point.” It relies on statistical data, sociological studies, and historical facts to address the connections between emigration from Italy and immigration to Italy, as well as Italian colonialism in Africa and the Mediterranean, and its postcolonial legacy. This intersection prompts a re-mapping of the Italian nation and poses Italy as a unique laboratory to rethink national belonging at large in our era of massive demographic mobility. The introduction explains the application of theories of space by de Certeau, Lefebvre, and Soja to the trans-national dimension of the Italian nation and highlights the main goals of the book. The introduction offers a fairly comprehensive survey of the fields that the book is in dialogue with by positioning itself vis-à-vis previous publications and also functions as an overview. It highlights the double approach of the book which is, on one hand to focus on texts that address both emigration and immigration or colonialism in conjunction; and, on the other, to connect texts that can be fruitfully read in tandem in order to create historical and cultural reverberations.
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Conference papers on the topic "Short Read Mapping (SRM)"

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Olson, Corey B., Maria Kim, Cooper Clauson, Boris Kogon, Carl Ebeling, Scott Hauck, and Walter L. Ruzzo. "Hardware Acceleration of Short Read Mapping." In 2012 IEEE 20th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2012. http://dx.doi.org/10.1109/fccm.2012.36.

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Arram, James, Kuen Hung Tsoi, Wayne Luk, and Peiyong Jiang. "Reconfigurable Acceleration of Short Read Mapping." In 2013 IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2013. http://dx.doi.org/10.1109/fccm.2013.57.

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Dai, Dong, Xi Li, Chao Wang, and Xuehai Zhou. "Cloud Based Short Read Mapping Service." In 2012 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2012. http://dx.doi.org/10.1109/cluster.2012.60.

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Chen, Yupeng, Bertil Schmidt, and Douglas L. Maksell. "An FPGA aligner for short read mapping." In 2012 22nd International Conference on Field Programmable Logic and Applications (FPL). IEEE, 2012. http://dx.doi.org/10.1109/fpl.2012.6339267.

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Aji, Ashwin M., Liqing Zhang, and Wu-chun Feng. "GPU-RMAP: Accelerating Short-Read Mapping on Graphics Processors." In 2010 IEEE 13th International Conference on Computational Science and Engineering (CSE). IEEE, 2010. http://dx.doi.org/10.1109/cse.2010.29.

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Sogabe, Yoko, and Tsutomu Maruyama. "An acceleration method of short read mapping using FPGA." In 2013 International Conference on Field-Programmable Technology (FPT). IEEE, 2013. http://dx.doi.org/10.1109/fpt.2013.6718385.

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Chen, Yupeng, Bertil Schmidt, and Douglas Leslie Maskell. "Accelerating short read mapping on an FPGA (abstract only)." In the ACM/SIGDA international symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2145694.2145740.

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Ng, Ho-Cheung, Izaak Coleman, Shuanglong Liu, and Wayne Luk. "Reconfigurable Acceleration of Short Read Mapping with Biological Consideration." In FPGA '21: The 2021 ACM/SIGDA International Symposium on Field Programmable Gate Arrays. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3431920.3439280.

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Preuber, Thomas B., Oliver Knodel, and Rainer G. Spallek. "Short-Read Mapping by a Systolic Custom FPGA Computation." In 2012 IEEE 20th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2012. http://dx.doi.org/10.1109/fccm.2012.37.

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Knodel, Oliver, Thomas B. Preusser, and Rainer G. Spallek. "Next-generation massively parallel short-read mapping on FPGAs." In 2011 IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP). IEEE, 2011. http://dx.doi.org/10.1109/asap.2011.6043268.

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Reports on the topic "Short Read Mapping (SRM)"

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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7600047.bard.

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Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule sequencing and shifted the focus to Nanoporelong-read sequencing of all 25 founder lines. This analysis provides invaluable information on genome-wide structural variation across our diversity 4) Integrated analyses and development of prediction models Agricultural heterosis relates to hybrids that outperform their inbred parents for yield. First generation (F1) hybrids are produced in many crop species and it is estimated that heterosis increases yield by 15-30% globally. Melon (Cucumismelo) is an economically important species of The Cucurbitaceae family and is among the most important fleshy fruits for fresh consumption Worldwide. The major goal of this project was to explore the patterns and magnitude of yield heterosis in melon and link it to whole genome sequence variation. A core subset of 25 diverse lines was selected from the Newe-Yaar melon diversity panel for whole-genome re-sequencing (WGS) and test-crosses, to produce structured half-diallele design of 300 F1 hybrids (MelHDA25). Yield variation was measured in replicated yield trials at the whole-plant and at the rootstock levels (through a common-scion grafted experiments), across the F1s and parental lines. As part of this project we also developed an algorithmic pipeline for detection and yield estimation of melons from aerial-images, towards future implementation of such high throughput, cost-effective method for remote yield evaluation in open-field melons. We found extensive, highly heritable root-derived yield variation across the diallele population that was characterized by prominent best-parent heterosis (BPH), where hybrids rootstocks outperformed their parents by 38% and 56 % under optimal irrigation and drought- stress, respectively. Through integration of the genotypic data (~4,000,000 SNPs) and yield analyses we show that root-derived hybrids yield is independent of parental genetic distance. However, we mapped novel root-derived yield QTLs through genome-wide association (GWA) analysis and a multi-QTLs model explained more than 45% of the hybrids yield variation, providing a potential route for marker-assisted hybrid rootstock breeding. Four selected hybrid rootstocks are further studied under multiple scion varieties and their validated positive effect on yield performance is now leading to ongoing evaluation of their commercial potential. On the genomic level, this project resulted in 3 layers of data: 1) whole-genome short-read Illumina sequencing (30X) of the 25 founder lines provided us with 25 genome alignments and high-density melon HapMap that is already shown to be an effective resource for QTL annotation and candidate gene analysis in melon. 2) fast advancements in long-read single-molecule sequencing allowed us to shift focus towards this technology and generate ~50X Nanoporesequencing of the 25 founders which in combination with the short-read data now enable de novo assembly of the 25 genomes that will soon lead to construction of the first melon pan-genome. 3) Transcriptomic (3' RNA-Seq) analysis of several selected hybrids and their parents provide preliminary information on differentially expressed genes that can be further used to explain the root-derived yield variation. Taken together, this project expanded our view on yield heterosis in melon with novel specific insights on root-derived yield heterosis. To our knowledge, thus far this is the largest systematic genetic analysis of rootstock effects on yield heterosis in cucurbits or any other crop plant, and our results are now translated into potential breeding applications. The genomic resources that were developed as part of this project are putting melon in the forefront of genomic research and will continue to be useful tool for the cucurbits community in years to come.
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