Relevant bibliographies by topics / Genomics; DNA sequencing; Bioinformatics

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

Academic literature on the topic 'Genomics; DNA sequencing; Bioinformatics'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Genomics; DNA sequencing; Bioinformatics"

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Shi, Lizhen, and Zhong Wang. "Computational Strategies for Scalable Genomics Analysis." Genes 10, no. 12 (2019): 1017. http://dx.doi.org/10.3390/genes10121017.

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The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications.
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Ow, T. J., K. Upadhyay, T. J. Belbin, M. B. Prystowsky, H. Ostrer, and R. V. Smith. "Bioinformatics in otolaryngology research. Part one: concepts in DNA sequencing and gene expression analysis." Journal of Laryngology & Otology 128, no. 10 (2014): 848–58. http://dx.doi.org/10.1017/s002221511400200x.

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AbstractBackground:Advances in high-throughput molecular biology, genomics and epigenetics, coupled with exponential increases in computing power and data storage, have led to a new era in biological research and information. Bioinformatics, the discipline devoted to storing, analysing and interpreting large volumes of biological data, has become a crucial component of modern biomedical research. Research in otolaryngology has evolved along with these advances.Objectives:This review highlights several modern high-throughput research methods, and focuses on the bioinformatics principles necessary to carry out such studies. Several examples from recent literature pertinent to otolaryngology are provided. The review is divided into two parts; this first part discusses the bioinformatics approaches applied in nucleotide sequencing and gene expression analysis.Conclusion:This paper demonstrates how high-throughput nucleotide sequencing and transcriptomics are changing biology and medicine, and describes how these changes are affecting otorhinolaryngology. Sound bioinformatics approaches are required to obtain useful information from the vast new sources of data.
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Kong, Siyuan, Qing Li, Gaolin Zhang, et al. "Exonuclease combinations reduce noises in 3D genomics technologies." Nucleic Acids Research 48, no. 8 (2020): e44-e44. http://dx.doi.org/10.1093/nar/gkaa106.

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Abstract Chromosome conformation-capture technologies are widely used in 3D genomics; however, experimentally, such methods have high-noise limitations and, therefore, require significant bioinformatics efforts to extract reliable distal interactions. Miscellaneous undesired linear DNAs, present during proximity-ligation, represent a main noise source, which needs to be minimized or eliminated. In this study, different exonuclease combinations were tested to remove linear DNA fragments from a circularized DNA preparation. This method efficiently removed linear DNAs, raised the proportion of annulation and increased the valid-pairs ratio from ∼40% to ∼80% for enhanced interaction detection in standard Hi-C. This strategy is applicable for development of various 3D genomics technologies, or optimization of Hi-C sequencing efficiency.
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Yang, Xinmiao, Mark R. Hartman, Kristin T. Harrington, et al. "Using Next-Generation Sequencing to Explore Genetics and Race in the High School Classroom." CBE—Life Sciences Education 16, no. 2 (2017): ar22. http://dx.doi.org/10.1187/cbe.16-09-0281.

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With the development of new sequencing and bioinformatics technologies, concepts relating to personal genomics play an increasingly important role in our society. To promote interest and understanding of sequencing and bioinformatics in the high school classroom, we developed and implemented a laboratory-based teaching module called “The Genetics of Race.” This module uses the topic of race to engage students with sequencing and genetics. In the experimental portion of this module, students isolate their own mitochondrial DNA using standard biotechnology techniques and collect next-generation sequencing data to determine which of their classmates are most and least genetically similar to themselves. We evaluated the efficacy of this module by administering a pretest/posttest evaluation to measure student knowledge related to sequencing and bioinformatics, and we also conducted a survey at the conclusion of the module to assess student attitudes. Upon completion of our Genetics of Race module, students demonstrated significant learning gains, with lower-performing students obtaining the highest gains, and developed more positive attitudes toward scientific research.
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Zheng, Weibo, Jing Chen, Thomas G. Doak, Weibo Song, and Ying Yan. "ADFinder: accurate detection of programmed DNA elimination using NGS high-throughput sequencing data." Bioinformatics 36, no. 12 (2020): 3632–36. http://dx.doi.org/10.1093/bioinformatics/btaa226.

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Abstract Motivation Programmed DNA elimination (PDE) plays a crucial role in the transitions between germline and somatic genomes in diverse organisms ranging from unicellular ciliates to multicellular nematodes. However, software specific for the detection of DNA splicing events is scarce. In this paper, we describe Accurate Deletion Finder (ADFinder), an efficient detector of PDEs using high-throughput sequencing data. ADFinder can predict PDEs with relatively low sequencing coverage, detect multiple alternative splicing forms in the same genomic location and calculate the frequency for each splicing event. This software will facilitate research of PDEs and all down-stream analyses. Results By analyzing genome-wide DNA splicing events in two micronuclear genomes of Oxytricha trifallax and Tetrahymena thermophila, we prove that ADFinder is effective in predicting large scale PDEs. Availability and implementation The source codes and manual of ADFinder are available in our GitHub website: https://github.com/weibozheng/ADFinder. Supplementary information Supplementary data are available at Bioinformatics online.
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Utturkar, Sagar M., W. Nathan Cude, Michael S. Robeson, et al. "Enrichment of Root Endophytic Bacteria from Populus deltoides and Single-Cell-Genomics Analysis." Applied and Environmental Microbiology 82, no. 18 (2016): 5698–708. http://dx.doi.org/10.1128/aem.01285-16.

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ABSTRACTBacterial endophytes that colonizePopulustrees contribute to nutrient acquisition, prime immunity responses, and directly or indirectly increase both above- and below-ground biomasses. Endophytes are embedded within plant material, so physical separation and isolation are difficult tasks. Application of culture-independent methods, such as metagenome or bacterial transcriptome sequencing, has been limited due to the predominance of DNA from the plant biomass. Here, we describe a modified differential and density gradient centrifugation-based protocol for the separation of endophytic bacteria fromPopulusroots. This protocol achieved substantial reduction in contaminating plant DNA, allowed enrichment of endophytic bacteria away from the plant material, and enabled single-cell genomics analysis. Four single-cell genomes were selected for whole-genome amplification based on their rarity in the microbiome (potentially uncultured taxa) as well as their inferred abilities to form associations with plants. Bioinformatics analyses, including assembly, contamination removal, and completeness estimation, were performed to obtain single-amplified genomes (SAGs) of organisms from the phylaArmatimonadetes,Verrucomicrobia, andPlanctomycetes, which were unrepresented in our previous cultivation efforts. Comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria.IMPORTANCEPlant roots harbor a diverse collection of microbes that live within host tissues. To gain a comprehensive understanding of microbial adaptations to this endophytic lifestyle from strains that cannot be cultivated, it is necessary to separate bacterial cells from the predominance of plant tissue. This study provides a valuable approach for the separation and isolation of endophytic bacteria from plant root tissue. Isolated live bacteria provide material for microbiome sequencing, single-cell genomics, and analyses of genomes of uncultured bacteria to provide genomics information that will facilitate future cultivation attempts.
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Greer, S. U., and H. P. Ji. "Structural variant analysis for linked-read sequencing data with gemtools." Bioinformatics 35, no. 21 (2019): 4397–99. http://dx.doi.org/10.1093/bioinformatics/btz239.

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Abstract Summary Linked-read sequencing generates synthetic long reads which are useful for the detection and analysis of structural variants (SVs). The software associated with 10× Genomics linked-read sequencing, Long Ranger, generates the essential output files (BAM, VCF, SV BEDPE) necessary for downstream analyses. However, to perform downstream analyses requires the user to customize their own tools to handle the unique features of linked-read sequencing data. Here, we describe gemtools, a collection of tools for the downstream and in-depth analysis of SVs from linked-read data. Gemtools uses the barcoded aligned reads and the Megabase-scale phase blocks to determine haplotypes of SV breakpoints and delineate complex breakpoint configurations at the resolution of single DNA molecules. The gemtools package is a suite of tools that provides the user with the flexibility to perform basic functions on their linked-read sequencing output in order to address even more questions. Availability and implementation The gemtools package is freely available for download at: https://github.com/sgreer77/gemtools. Supplementary information Supplementary data are available at Bioinformatics online.
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Voelkerding, Karl V., Shale A. Dames, and Jacob D. Durtschi. "Next-Generation Sequencing: From Basic Research to Diagnostics." Clinical Chemistry 55, no. 4 (2009): 641–58. http://dx.doi.org/10.1373/clinchem.2008.112789.

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Abstract Background: For the past 30 years, the Sanger method has been the dominant approach and gold standard for DNA sequencing. The commercial launch of the first massively parallel pyrosequencing platform in 2005 ushered in the new era of high-throughput genomic analysis now referred to as next-generation sequencing (NGS). Content: This review describes fundamental principles of commercially available NGS platforms. Although the platforms differ in their engineering configurations and sequencing chemistries, they share a technical paradigm in that sequencing of spatially separated, clonally amplified DNA templates or single DNA molecules is performed in a flow cell in a massively parallel manner. Through iterative cycles of polymerase-mediated nucleotide extensions or, in one approach, through successive oligonucleotide ligations, sequence outputs in the range of hundreds of megabases to gigabases are now obtained routinely. Highlighted in this review are the impact of NGS on basic research, bioinformatics considerations, and translation of this technology into clinical diagnostics. Also presented is a view into future technologies, including real-time single-molecule DNA sequencing and nanopore-based sequencing. Summary: In the relatively short time frame since 2005, NGS has fundamentally altered genomics research and allowed investigators to conduct experiments that were previously not technically feasible or affordable. The various technologies that constitute this new paradigm continue to evolve, and further improvements in technology robustness and process streamlining will pave the path for translation into clinical diagnostics.
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Mose, Lisle E., Charles M. Perou, and Joel S. Parker. "Improved indel detection in DNA and RNA via realignment with ABRA2." Bioinformatics 35, no. 17 (2019): 2966–73. http://dx.doi.org/10.1093/bioinformatics/btz033.

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Abstract Motivation Genomic variant detection from next-generation sequencing has become established as an extremely important component of research and clinical diagnoses in both cancer and Mendelian disorders. Insertions and deletions (indels) are a common source of variation and can frequently impact functionality, thus making their detection vitally important. While substantial effort has gone into detecting indels from DNA, there is still opportunity for improvement. Further, detection of indels from RNA-Seq data has largely been an afterthought and offers another critical area for variant detection. Results We present here ABRA2, a redesign of the original ABRA implementation that offers support for realignment of both RNA and DNA short reads. The process results in improved accuracy and scalability including support for human whole genomes. Results demonstrate substantial improvement in indel detection for a variety of data types, including those that were not previously supported by ABRA. Further, ABRA2 results in broad improvements to variant calling accuracy across a wide range of post-processing workflows including whole genomes, targeted exomes and transcriptome sequencing. Availability and implementation ABRA2 is implemented in a combination of Java and C/C++ and is freely available to all from: https://github.com/mozack/abra2. Supplementary information Supplementary data are available at Bioinformatics online.
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Bhattacharya, Debashish, Rajat S. Roy, Dana C. Price, and Alexander Schliep. "Single-cell genomics of marine plankton: Studying the single life of eukaryotic microbes." Biochemist 36, no. 1 (2014): 16–22. http://dx.doi.org/10.1042/bio03601016.

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The oceans are full of innumerable numbers of single cells living in microenvironments. Understanding who they are, what they eat and what infects them can inform us about the true diversity of plankton, their biotic interactions and how they may respond to a changing environment. Analysing to significant depth the genomes and ‘gut’ (i.e. the food vacuole and other contents) of individual wild-caught cells would have been thought impossible only a few years ago. However, the rapidly expanding field of single-cell genomics, powered by modern cell-sorting procedures, high-throughput DNA sequencing and bioinformatics methods holds the promise to revolutionize understanding of the biodiversity and ecology of eukaryotic microbes and their places in the tree of life.
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Dissertations / Theses on the topic "Genomics; DNA sequencing; Bioinformatics"

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Jones, Steven John Mathias. "Computational analysis of the Caenorhabditis elegans genome sequence." Thesis, Open University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301886.

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Klevebring, Daniel. "On Transcriptome Sequencing." Doctoral thesis, KTH, Genteknologi, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-11446.

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This thesis is about the use of massive DNA sequencing to investigate the transcriptome. During recent decades, several studies have made it clear that the transcriptome comprises a more complex set of biochemical machinery than was previously believed. The majority of the genome can be expressed as transcripts; and overlapping and antisense transcription is widespread. New technologies for the interroga- tion of nucleic acids have made it possible to investigate such cellular phenomena in much greater detail than ever before. For each application, special requirements need to be met. The work presented in this thesis focuses on the transcrip- tome and the development of technology for its analysis. In paper I, we report our development of an automated approach for sample preparation. The procedure was benchmarked against a publicly available reference data set, and we note that our approach outperformed similar manual procedures in terms of reproducibility. In the work reported in papers II-IV, we used different massive sequencing technologies to investigate the transcriptome. In paper II we describe a concatemerization approach that increased throughput by 65% using 454 sequencing,and we identify classes of transcripts not previously described in Populus. Papers III and IV both report studies based on SOLiD sequencing. In the former, we investigated transcripts and proteins for 13% of the human gene and detected a massive overlap for the upper 50% transcriptional levels. In the work described in paper IV, we investigated transcription in non-genic regions of the genome and detected expression from a high number of previ- ously unknown loci.<br>QC 20100723
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Bhasin, Jeffrey M. "Methylome Sequencing Reveals the Context-Specific Functions of DNA Methylation in Indolent Versus Aggressive Prostate Cancer." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case148120498969955.

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Zhuang, Jiali. "Structural Variation Discovery and Genotyping from Whole Genome Sequencing: Methodology and Applications: A Dissertation." eScholarship@UMMS, 2009. http://escholarship.umassmed.edu/gsbs_diss/875.

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A comprehensive understanding about how genetic variants and mutations contribute to phenotypic variations and alterations entails experimental technologies and analytical methodologies that are able to detect genetic variants/mutations from various biological samples in a timely and accurate manner. High-throughput sequencing technology represents the latest achievement in a series of efforts to facilitate genetic variants discovery and genotyping and promises to transform the way we tackle healthcare and biomedical problems. The tremendous amount of data generated by this new technology, however, needs to be processed and analyzed in an accurate and efficient way in order to fully harness its potential. Structural variation (SV) encompasses a wide range of genetic variations with different sizes and generated by diverse mechanisms. Due to the technical difficulties of reliably detecting SVs, their characterization lags behind that of SNPs and indels. In this dissertation I presented two novel computational methods: one for detecting transposable element (TE) transpositions and the other for detecting SVs in general using a local assembly approach. Both methods are able to pinpoint breakpoint junctions at single-nucleotide resolution and estimate variant allele frequencies in the sample. I also applied those methods to study the impact of TE transpositions on the genomic stability, the inheritance patterns of TE insertions in the population and the molecular mechanisms and potential functional consequences of somatic SVs in cancer genomes.
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Zhuang, Jiali. "Structural Variation Discovery and Genotyping from Whole Genome Sequencing: Methodology and Applications: A Dissertation." eScholarship@UMMS, 2015. https://escholarship.umassmed.edu/gsbs_diss/875.

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A comprehensive understanding about how genetic variants and mutations contribute to phenotypic variations and alterations entails experimental technologies and analytical methodologies that are able to detect genetic variants/mutations from various biological samples in a timely and accurate manner. High-throughput sequencing technology represents the latest achievement in a series of efforts to facilitate genetic variants discovery and genotyping and promises to transform the way we tackle healthcare and biomedical problems. The tremendous amount of data generated by this new technology, however, needs to be processed and analyzed in an accurate and efficient way in order to fully harness its potential. Structural variation (SV) encompasses a wide range of genetic variations with different sizes and generated by diverse mechanisms. Due to the technical difficulties of reliably detecting SVs, their characterization lags behind that of SNPs and indels. In this dissertation I presented two novel computational methods: one for detecting transposable element (TE) transpositions and the other for detecting SVs in general using a local assembly approach. Both methods are able to pinpoint breakpoint junctions at single-nucleotide resolution and estimate variant allele frequencies in the sample. I also applied those methods to study the impact of TE transpositions on the genomic stability, the inheritance patterns of TE insertions in the population and the molecular mechanisms and potential functional consequences of somatic SVs in cancer genomes.
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Clarke, Andrew, Stefan Prost, Jo-Ann Stanton, et al. "From cheek swabs to consensus sequences: an A to Z protocol for high-throughput DNA sequencing of complete human mitochondrial genomes." BioMed Central, 2014. http://hdl.handle.net/10150/610024.

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BACKGROUND:Next-generation DNA sequencing (NGS) technologies have made huge impacts in many fields of biological research, but especially in evolutionary biology. One area where NGS has shown potential is for high-throughput sequencing of complete mtDNA genomes (of humans and other animals). Despite the increasing use of NGS technologies and a better appreciation of their importance in answering biological questions, there remain significant obstacles to the successful implementation of NGS-based projects, especially for new users.RESULTS:Here we present an 'A to Z' protocol for obtaining complete human mitochondrial (mtDNA) genomes - from DNA extraction to consensus sequence. Although designed for use on humans, this protocol could also be used to sequence small, organellar genomes from other species, and also nuclear loci. This protocol includes DNA extraction, PCR amplification, fragmentation of PCR products, barcoding of fragments, sequencing using the 454 GS FLX platform, and a complete bioinformatics pipeline (primer removal, reference-based mapping, output of coverage plots and SNP calling).CONCLUSIONS:All steps in this protocol are designed to be straightforward to implement, especially for researchers who are undertaking next-generation sequencing for the first time. The molecular steps are scalable to large numbers (hundreds) of individuals and all steps post-DNA extraction can be carried out in 96-well plate format. Also, the protocol has been assembled so that individual 'modules' can be swapped out to suit available resources.
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Martinez, Juan Carlos. "Towards the Prediction of Mutations in Genomic Sequences." FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/987.

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Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today’s cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who’s DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.
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Oikonomopoulos, Spyridon. "Inferring structural properties of protein-DNA binding using high-throughput sequencing : the paradigm of GATA1, KLF1 and their complexes GATA1/FOG1 and GATA1/KLF1 : insights into the transcriptional regulation of the erythroid cell lineage." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:72b92906-4ef6-4c1d-9155-484521027e2e.

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GATA1 and KLF1 are transcription factors that regulate genes which are important for the development of erythroid cells. The GATA1 transcriptional co-factor FOG1 has been shown to be essential in a wide range of GATA1 dependent cellular functions. Here we tried to understand the diverse mechanisms by which GATA1 and KLF1 recognize their binding sites, how the GATA1 recognition mechanisms are affected by complexation with either FOG1 or KLF1 and how the GATA1 recognition mechanisms affect the transcriptional regulation of the erythroid differentiation. We profiled the DNA binding specificities/affinities of a GATA1 fragment (mGATA1NC), that contains only the two DNA binding domains (N-terminal and C-terminal Zn finger), and the DNA binding specificities/affinities of a KLF1 fragment (mKLF1257-358), that contains the three DNA binding domains, using a novel methodology that combines EMSA with high throughput sequencing (EMSA-seq (Wong et al., 2011a)). We also profiled the DNA binding specificities of the C-terminal Zn finger of GATA1 alone (mGATA1C), the wt-mGATA1, the wt-mGATA1/wt-mFOG1 complex and the mGATA1NC/mKLF1257-358 complex. At first, we confirmed that the N-terminal Zn finger of GATA1 has a strong preference for the “GATC” motif, whereas the C-terminal Zn finger of GATA1 has a strong preference for the “GATA” motif. Next, we found that in the mGATA1NC, both DNA binding domains can bind simultaneously a wide range of different positional combinations of the co-occurring “GATA” and “GATC” motifs, on the same DNA sequence. The wt-mGATA1 did not show the ability to bind in the same co-occurring motifs implying an effect of the non-DNA binding domains of the protein in the regulation of its DNA binding specificities. On the contrary, complexation of wt-mGATA1 with the wt-mFOG1 partially restored its ability to bind in a now limited range of different positional combinations of the co-occurring “GATA” and “GATC” motifs, on the same DNA sequence. Similar observations were made for other pairs of GATA1 N-terminal and C-terminal Zn finger specific motifs. We then projected the GATA1 DNA binding specificities/affinities in vivo and we classified the GATA1 ChIP-seq peaks in low, medium or high affinity based on the number of the GATA1 motifs. We noticed that high affinity GATA1 ChIP-seq peaks tend to appear in regions with low nucleosome occupancy. We also noticed that GATA1 ChIP-seq peaks in the enhancer regions are usually high affinity whereas GATA1 ChIP-seq peaks in the proximal promoter regions are usually low affinity. Additionally, we observed that high affinity GATA1 ChIP-seq peaks are usually found in regions with increased levels of H3K4me2 and are associated with a higher decrease in the H3K4me3 levels on the TSS of the nearby genes. None of these GATA1 related in vivo observations were found for the KLF1 ChIP-seq positions. These findings significantly advance our understanding of the DNA binding properties of GATA1, KLF1 and their complexes and give an insight on the importance of the GATA1 DNA binding affinities in the regulation of the erythroid transcriptional program. Overall the work establishes an experimental and analytical framework to investigate how transcriptional co-factors can change the DNA binding specificities of specific transcription factors and how integration of the transcription factor DNA binding affinities with in vivo data can give novel insights into the transcriptional regulation.
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Delhomme, Tiffany. "Using the systematic nature of errors in NGS data to efficiently detect mutations : computational methods and application to early cancer detection." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1098/document.

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La caractérisation exaustive des variations de l'ADN peut aider à progresser dans de nombreux champs liés à la génomique du cancer. Le séquençage nouvelle génération (NGS en anglais pour Next Generation Sequencing) est actuellement la technique la plus efficace pour déterminer une séquence ADN, du aux faibles coûts et durées des expériences comparé à la méthode de séquençage traditionnelle de Sanger. Cependant, la détection de mutations à partir de données NGS reste encore un problème difficile, en particulier pour les mutations somatiques présentes en très faible abondance comme lorsque l'on essaye d'identifier des mutations sous-clonales d'une tumeur, des mutations dérivées de la tumeur dans l'ADN circulant libre, ou des mutations somatiques dans des tissus normaux. La difficulté principale est de précisement distinguer les vraies mutations des artefacts de séquençage du au fait qu'ils atteignent des niveaux similaires. Dans cette thèse nous avons étudié la nature systématique des erreurs dans les données NGS afin de proposer des méthodologies efficaces capables d'identifier des mutations potentiellement en faible abondance. Dans un premier chapitre, nous decrivons needlestack, un nouvel outil d'appel de variants basé sur la modélisation des erreurs systématiques sur plusieurs échantillons pour extraire des mutations candidates. Dans un deuxième chapitre, nous proposons deux méthodes de filtrage des variants basées sur des résumés statistiques et sur de l'apprentissage automatique, dans le but de d'améliorer la précision de la détection des mutations par l'identification des erreurs non-systématiques. Finalement, dans un dernier chapitre nous appliquons ces approches pour développer des biomarqueurs de détection précoce du cancer en utilisant l'ADN circulant tumoral<br>Comprehensive characterization of DNA variations can help to progress in multiple cancer genomics fields. Next Generation Sequencing (NGS) is currently the most efficient technique to determine a DNA sequence, due to low experiment cost and time compared to the traditional Sanger sequencing. Nevertheless, detection of mutations from NGS data is still a difficult problem, in particular for somatic mutations present in very low abundance like when trying to identify tumor subclonal mutations, tumor-derived mutations in cell free DNA, or somatic mutations from histological normal tissue. The main difficulty is to precisely distinguish between true mutations from sequencing artifacts as they reach similar levels. In this thesis we have studied the systematic nature of errors in NGS data to propose efficient methodologies in order to accurately identify mutations potentially in low proportion. In a first chapter, we describe needlestack, a new variant caller based on the modelling of systematic errors across multiple samples to extract candidate mutations. In a second chapter, we propose two post-calling variant filtering methods based on new summary statistics and on machine learning, with the aim of boosting the precision of mutation detection through the identification of non-systematic errors. Finally, in a last chapter we apply these approaches to develop cancer early detection biomarkers using circulating tumor DNA
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Roy, Christian K. "Putting the Pieces Together: Exons and piRNAs: A Dissertation." eScholarship@UMMS, 2014. https://escholarship.umassmed.edu/gsbs_diss/726.

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Analysis of gene expression has undergone a technological revolution. What was impossible 6 years ago is now routine. High-throughput DNA sequencing machines capable of generating hundreds of millions of reads allow, indeed force, a major revision toward the study of the genome’s functional output—the transcriptome. This thesis examines the history of DNA sequencing, measurement of gene expression by sequencing, isoform complexity driven by alternative splicing and mammalian piRNA precursor biogenesis. Examination of these topics is framed around development of a novel RNA-templated DNA-DNA ligation assay (SeqZip) that allows for efficient analysis of abundant, complex, and functional long RNAs. The discussion focuses on the future of transcriptome analysis, development and applications of SeqZip, and challenges presented to biomedical researchers by extremely large and rich datasets.
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Books on the topic "Genomics; DNA sequencing; Bioinformatics"

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Bioinformatics: Genomics and post-genomics. John Wiley & Sons, 2006.

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Rodríguez-Ezpeleta, Naiara, Michael Hackenberg, and Ana M. Aransay. Bioinformatics for high throughput sequencing. Springer, 2012.

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Alphey, Luke. DNA sequencing from experimental methods to bioinformatics. Springer, 1997.

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Campbell, A. Malcolm. Discovering genomics, proteomics, and bioinformatics. 2nd ed. CSHL Press, 2007.

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J, Heyer Laurie, ed. Discovering genomics, proteomics, and bioinformatics. 2nd ed. CSHL Press, 2007.

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Kahl, Günter, and Matthias Harbers. Tag-based next generation sequencing. Wiley-Blackwell, 2012.

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Janitz, Michal. Next-generation genome sequencing: Towards personalized medicine. Wiley-VCH, 2008.

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T, Kho Alvin, and Butte Atul J, eds. Microarrays for an integrative genomics. MIT Press, 2003.

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Majoros, William H. Methods for computational gene prediction. Cambridge University Press, 2007.

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Methods for computational gene prediction. Cambridge University Press, 2007.

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Book chapters on the topic "Genomics; DNA sequencing; Bioinformatics"

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Doyle, Maria A., Jason Li, Ken Doig, Andrew Fellowes, and Stephen Q. Wong. "Studying Cancer Genomics Through Next-Generation DNA Sequencing and Bioinformatics." In Methods in Molecular Biology. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0847-9_6.

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Sterflinger, Katja, and Guadalupe Piñar. "Molecular-Based Techniques for the Study of Microbial Communities in Artworks." In Microorganisms in the Deterioration and Preservation of Cultural Heritage. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69411-1_3.

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AbstractThanks to the revolutionary invention of the polymerase chain reaction and the sequencing of DNA and RNA by means of “Sanger sequencing” in the 1970th and 1980th, it became possible to detect microorganisms in art and cultural assets that do not grow on culture media or that are non-viable. The following generation of sequencing systems (next generation sequencing, NGS) already allowed the detection of microbial communities on objects without the intermediate step of cloning, but still most of the NGS technologies used for the study of microbial communities in objects of art rely on “target sequencing” linked to the selectivity of the primers used for amplification. Today, with the third generation of sequencing technology, whole genome and metagenome sequencing is possible, allowing the detection of taxonomic units of all domains and kingdoms as well as functional genes in the produced metagenome. Currently, Nanopore sequencing technology is a good, affordable, and simple way to characterize microbial communities, especially in the field of Heritage Science. It also has the advantage that a bioinformatic analysis can be performed automatically. In addition to genomics and metagenomics, other “-omics” techniques such as transcriptomics, proteomics, and metabolomics have a great potential for the study of processes in art and cultural heritage, but are still in their infancy as far as their application in this field is concerned.
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Papenfuss, Anthony T., Arthur Hsu, and Matthew Wakefield. "Marsupial Sequencing Projects and Bioinformatics Challenges." In Marsupial Genetics and Genomics. Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9023-2_6.

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Tuteja, Geetu. "DNA–Protein Interaction Analysis (ChIP-Seq)." In Bioinformatics for High Throughput Sequencing. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_8.

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Kerick, Martin, Axel Fischer, and Michal-Ruth Schweiger. "Generation and Analysis of Genome-Wide DNA Methylation Maps." In Bioinformatics for High Throughput Sequencing. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_9.

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Déchaux, Jean-Hugues. "Being Born in the Era of Genomics." In From Measuring Rods to DNA Sequencing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7582-2_5.

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Fotouhi, Ali, Mina Majidi, and M. Oğuzhan Külekci. "Quality Assessment of High-Throughput DNA Sequencing Data via Range Analysis." In Bioinformatics and Biomedical Engineering. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78723-7_37.

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Chen, Shifu, Ming Liu, and Yanqing Zhou. "Bioinformatics Analysis for Cell-Free Tumor DNA Sequencing Data." In Methods in Molecular Biology. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7717-8_5.

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Allcock, Richard James Nigel. "Production and Analytic Bioinformatics for Next-Generation DNA Sequencing." In Methods in Molecular Biology. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0847-9_2.

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Sang, Fei. "Bioinformatics Analysis of DNA Methylation Through Bisulfite Sequencing Data." In Methods in Molecular Biology. Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0876-0_32.

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Conference papers on the topic "Genomics; DNA sequencing; Bioinformatics"

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"T-DNA site identification by Cas9-targeted and whole-genome Nanopore sequencing of Arabidopsis thaliana." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Novosibirsk ICG SB RAS 2021, 2021. http://dx.doi.org/10.18699/plantgen2021-077.

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"Extraction of high-molecular-weight DNA from poplar plants for Nanopore sequencing." In Current Challenges in Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences Novosibirsk State University, 2019. http://dx.doi.org/10.18699/icg-plantgen2019-51.

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"Sequencing and iterative assembly of Ixiolirion tataricum plastome from total DNA using 2nd and 3rd generation HTS platforms." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-131.

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"Preparation of DNA libraries for sequencing of SAD and FAD genes in flax." In Current Challenges in Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences Novosibirsk State University, 2019. http://dx.doi.org/10.18699/icg-plantgen2019-49.

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Sie, Daoud, Ilari Scheinin, Stef van Lieshout, et al. "Abstract 52: QDNAseq: A bioinformatics pipeline for DNA copy number analysis from shallow whole genome sequencing with noise levels near the probabilistic lower limit imposed by read counting." In Abstracts: AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; June 13-16, 2015; Salt Lake City, UT. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1557-3265.pmsclingen15-52.

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Ivanov, Maxim, Magnus Ingelman-Sundberg, Mart Kals, and Lili Milani. "Targeted profiling of 5-(hydroxy)methylcytosine in genomic DNA from human livers: Next-generation sequencing of target enriched DNA reveals unexpectedly high interindividual variability of cytosine methylation and hydroxymethylation." In 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2014. http://dx.doi.org/10.1109/bibm.2014.6999389.

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"Polymorphism of flax pathogens assessed using deep sequencing." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-127.

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"Epigenetic profiling of plant LTR retrotransposon copies using Nanopore sequencing." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Novosibirsk ICG SB RAS 2021, 2021. http://dx.doi.org/10.18699/plantgen2021-146.

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"Study of the leaf rust resistance gene Lr52 by targeted sequencing." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-033.

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"Breakthroughs in plant retrotranscriptome and mobilome characterization enabled by Nanopore sequencing." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Novosibirsk ICG SB RAS 2021, 2021. http://dx.doi.org/10.18699/plantgen2021-097.

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