Log in

Relevant bibliographies by topics / Bioinformatics. Indexing

Contents

Journal articles
Dissertations / Theses
Book chapters
Conference papers

Academic literature on the topic 'Bioinformatics. Indexing'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Bioinformatics. Indexing.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Bioinformatics. Indexing"

1

Morgulis, Aleksandr, George Coulouris, Yan Raytselis, Thomas L. Madden, Richa Agarwala, and Alejandro A. Schäffer. "Database indexing for production MegaBLAST searches." Bioinformatics 24, no. 16 (2008): 1757–64. http://dx.doi.org/10.1093/bioinformatics/btn322.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Morgulis, A., G. Coulouris, Y. Raytselis, T. L. Madden, R. Agarwala, and A. A. Schaffer. "Database indexing for production MegaBLAST searches." Bioinformatics 24, no. 24 (2008): 2942. http://dx.doi.org/10.1093/bioinformatics/btn554.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Dai, Suyang, Ronghui You, Zhiyong Lu, Xiaodi Huang, Hiroshi Mamitsuka, and Shanfeng Zhu. "FullMeSH: improving large-scale MeSH indexing with full text." Bioinformatics 36, no. 5 (2019): 1533–41. http://dx.doi.org/10.1093/bioinformatics/btz756.

Full text

Abstract:

Abstract Motivation With the rapidly growing biomedical literature, automatically indexing biomedical articles by Medical Subject Heading (MeSH), namely MeSH indexing, has become increasingly important for facilitating hypothesis generation and knowledge discovery. Over the past years, many large-scale MeSH indexing approaches have been proposed, such as Medical Text Indexer, MeSHLabeler, DeepMeSH and MeSHProbeNet. However, the performance of these methods is hampered by using limited information, i.e. only the title and abstract of biomedical articles. Results We propose FullMeSH, a large-scale MeSH indexing method taking advantage of the recent increase in the availability of full text articles. Compared to DeepMeSH and other state-of-the-art methods, FullMeSH has three novelties: (i) Instead of using a full text as a whole, FullMeSH segments it into several sections with their normalized titles in order to distinguish their contributions to the overall performance. (ii) FullMeSH integrates the evidence from different sections in a ‘learning to rank’ framework by combining the sparse and deep semantic representations. (iii) FullMeSH trains an Attention-based Convolutional Neural Network for each section, which achieves better performance on infrequent MeSH headings. FullMeSH has been developed and empirically trained on the entire set of 1.4 million full-text articles in the PubMed Central Open Access subset. It achieved a Micro F-measure of 66.76% on a test set of 10 000 articles, which was 3.3% and 6.4% higher than DeepMeSH and MeSHLabeler, respectively. Furthermore, FullMeSH demonstrated an average improvement of 4.7% over DeepMeSH for indexing Check Tags, a set of most frequently indexed MeSH headings. Availability and implementation The software is available upon request. Supplementary information Supplementary data are available at Bioinformatics online.

APA, Harvard, Vancouver, ISO, and other styles

4

Lam, T. W., W. K. Sung, S. L. Tam, C. K. Wong, and S. M. Yiu. "Compressed indexing and local alignment of DNA." Bioinformatics 24, no. 6 (2008): 791–97. http://dx.doi.org/10.1093/bioinformatics/btn032.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Gülsoy, Günhan, and Tamer Kahveci. "RINQ: Reference-based Indexing for Network Queries." Bioinformatics 27, no. 13 (2011): i149—i158. http://dx.doi.org/10.1093/bioinformatics/btr203.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Klötzl, Fabian, and Bernhard Haubold. "Phylonium: fast estimation of evolutionary distances from large samples of similar genomes." Bioinformatics 36, no. 7 (2019): 2040–46. http://dx.doi.org/10.1093/bioinformatics/btz903.

Full text

Abstract:

Abstract Motivation Tracking disease outbreaks by whole-genome sequencing leads to the collection of large samples of closely related sequences. Five years ago, we published a method to accurately compute all pairwise distances for such samples by indexing each sequence. Since indexing is slow, we now ask whether it is possible to achieve similar accuracy when indexing only a single sequence. Results We have implemented this idea in the program phylonium and show that it is as accurate as its predecessor and roughly 100 times faster when applied to all 2678 Escherichia coli genomes contained in ENSEMBL. One of the best published programs for rapidly computing pairwise distances, mash, analyzes the same dataset four times faster but, with default settings, it is less accurate than phylonium. Availability and implementation Phylonium runs under the UNIX command line; its C++ sources and documentation are available from github.com/evolbioinf/phylonium. Supplementary information Supplementary data are available at Bioinformatics online.

APA, Harvard, Vancouver, ISO, and other styles

7

Garzon, Max H., Kiran C. Bobba, Andrew Neel, and Vinhthuy Phan. "DNA-Based Indexing." International Journal of Nanotechnology and Molecular Computation 2, no. 3 (2010): 25–45. http://dx.doi.org/10.4018/jnmc.2010070102.

Full text

Abstract:

DNA has been acknowledged as a suitable medium for massively parallel computing and as a “smart” glue for self-assembly. In this paper, a third capability of DNA is described in detail as memory capable of encoding and processing large amounts of data so that information can be retrieved associatively based on content. The technique is based on a novel representation of data on DNA that can shed information on the way DNA-, RNA- and other biomolecules encode information, which may be potentially important in applications to fields like bioinformatics and genetics, and natural language processing. Analyses are also provided of the sensitivity, robustness, and bounds on the theoretical capacity of the memories. Finally, the potential use of the memories are illustrated with two applications, one in genomic analysis for identification and classification, another in information retrieval from text data in abiotic form.

APA, Harvard, Vancouver, ISO, and other styles

8

Chang, Xian, Jordan Eizenga, Adam M. Novak, Jouni Sirén, and Benedict Paten. "Distance indexing and seed clustering in sequence graphs." Bioinformatics 36, Supplement_1 (2020): i146—i153. http://dx.doi.org/10.1093/bioinformatics/btaa446.

Full text

Abstract:

Abstract Motivation Graph representations of genomes are capable of expressing more genetic variation and can therefore better represent a population than standard linear genomes. However, due to the greater complexity of genome graphs relative to linear genomes, some functions that are trivial on linear genomes become much more difficult in genome graphs. Calculating distance is one such function that is simple in a linear genome but complicated in a graph context. In read mapping algorithms such distance calculations are fundamental to determining if seed alignments could belong to the same mapping. Results We have developed an algorithm for quickly calculating the minimum distance between positions on a sequence graph using a minimum distance index. We have also developed an algorithm that uses the distance index to cluster seeds on a graph. We demonstrate that our implementations of these algorithms are efficient and practical to use for a new generation of mapping algorithms based upon genome graphs. Availability and implementation Our algorithms have been implemented as part of the vg toolkit and are available at https://github.com/vgteam/vg.

APA, Harvard, Vancouver, ISO, and other styles

9

Camoglu, O., T. Kahveci, and A. K. Singh. "PSI: indexing protein structures for fast similarity search." Bioinformatics 19, Suppl 1 (2003): i81—i83. http://dx.doi.org/10.1093/bioinformatics/btg1009.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Liu, F., T. K. Jenssen, V. Nygaard, J. Sack, and E. Hovig. "FigSearch: a figure legend indexing and classification system." Bioinformatics 20, no. 16 (2004): 2880–82. http://dx.doi.org/10.1093/bioinformatics/bth316.

Full text

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Bioinformatics. Indexing"

1

Wu, Man-kit Edward, and 胡文傑. "Improved indexes for next generation bioinformatics applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43224222.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Wu, Man-kit Edward. "Improved indexes for next generation bioinformatics applications." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43224222.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Edenståhl, Selma. "Enterprise Search for Pharmacometric Documents : A Feature and Performance Evaluation." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417033.

Full text

Abstract:

Information retrieval within a company can be referred to as enterprise search. With the use of enterprise search, employees can find the information they need in company internal data. If a business can take advantage of the knowledge within the organization, it can save time and effort, and be a source for innovation and development within the company. In this project, two open source search engines, Recoll and Apache Solr, are selected, set up, and evaluated based on requirements and needs at the pharmacometric consulting company Pharmetheus AB. A requirement analysis is performed to collect system requirements at the company. Through a literature survey, two candidate search engines are selected. Lastly, a Proof of Concept is performed to demonstrate the feasibility of the search engines at the company. The search tools are evaluated on criteria including indexing performance, search functionality and configurability. This thesis presents assessment questions to be used when evaluating a search tool. It is shown that the indexing time for both Recoll and Apache Solr appears to scale linearly for less than one hundred thousand pdf documents. The benefit of an index is demonstrated when search times for both search engines greatly outperforms the Linux command-line tools grep and find. It is also explained how the strict folder structure and naming conventions at the company can be used in Recoll to only index specific documents and sub-parts of a file share. Furthermore, I demonstrate how the Recoll web GUI can be modified to include functionality for filtering on document type. The results show that Recoll meets most of the company’s system requirements and for that reason it could serve as an enterprise search engine at the company. However, the search engine lacks support for authentication, something that has to be further investigated and implemented before the system can be put into production.

APA, Harvard, Vancouver, ISO, and other styles

4

Helal, Manal Computer Science &amp Engineering Faculty of Engineering UNSW. "Indexing and partitioning schemes for distributed tensor computing with application to multiple sequence alignment." Awarded by:University of New South Wales. Computer Science & Engineering, 2009. http://handle.unsw.edu.au/1959.4/44781.

Full text

Abstract:

This thesis investigates indexing and partitioning schemes for high dimensional scientific computational problems. Building on the foundation offered by Mathematics of Arrays (MoA) for tensor-based computation, the ultimate contribution of the thesis is a unified partitioning scheme that works invariant of the dataset dimension and shape. Consequently, portability is ensured between different high performance machines, cluster architectures, and potentially computational grids. The Multiple Sequence Alignment (MSA) problem in computational biology has an optimal dynamic programming based solution, but it becomes computationally infeasible as its dimensionality (the number of sequences) increases. Even sub-optimal approximations may be unmanageable for more than eight sequences. Furthermore, no existing MSA algorithms have been formulated in a manner invariant over the number of sequences. This thesis presents an optimal distributed MSA method based on MoA. The latter offers a set of constructs that help represent multidimensional arrays in memory in a linear, concise and efficient way. Using MoA allows the partitioning of the dynamic programming algorithm to be expressed independently of dimension. MSA is the highest dimensional scientific problem considered for MoA-based partitioning to date. Two partitioning schemes are presented: the first is a master/slave approach which is based on both master/slave scheduling and slave/slave coupling. The second approach is a peer-to-peer design, in which the scheduling and dependency communication are calculated independently by each process, with no need for a master scheduler. A search space reduction technique is introduced to cater for the exponential expansion as the problem dimensionality increases. This technique relies on defining a hyper-diagonal through the tensor space, and choosing a band of neighbouring partitions around the diagonal to score. In contrast, other sub-optimal methods in the literature only consider projections on the surface of the hyper-cube. The resulting massively parallel design produces a scalable solution that has been implemented on high performance machines and cluster architectures. Experimental results for these implementations are presented for both simulated and real datasets. Comparisons between the reduced search space technique of this thesis with other sub-optimal methods for the MSA problem are presented.

APA, Harvard, Vancouver, ISO, and other styles

5

Abu, Doleh Anas. "High Performance and Scalable Matching and Assembly of Biological Sequences." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1469092998.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Ozturk, Ozgur. "Feature extraction and similarity-based analysis for proteome and genome databases." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1190138805.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Mao, Rui 1975. "Distance-based indexing and its applications in bioinformatics." Thesis, 2007. http://hdl.handle.net/2152/3788.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Ramakrishnan, Smriti Rajan. "A systems approach to computational protein identification." Thesis, 2010. http://hdl.handle.net/2152/ETD-UT-2010-05-1036.

Full text

Abstract:

Proteomics is the science of understanding the dynamic protein content of an organism's cells (its proteome), which is one of the largest current challenges in biology. Computational proteomics is an active research area that involves in-silico methods for the analysis of high-throughput protein identification data. Current methods are based on a technology called tandem mass spectrometry (MS/MS) and suffer from low coverage and accuracy, reliably identifying only 20-40% of the proteome. This dissertation addresses recall, precision, speed and scalability of computational proteomics experiments. This research goes beyond the traditional paradigm of analyzing MS/MS experiments in isolation, instead learning priors of protein presence from the joint analysis of various systems biology data sources. This integrative `systems' approach to protein identification is very effective, as demonstrated by two new methods. The first, MSNet, introduces a social model for protein identification and leverages functional dependencies from genome-scale, probabilistic, gene functional networks. The second, MSPresso, learns a gene expression prior from a joint analysis of mRNA and proteomics experiments on similar samples. These two sources of prior information result in more accurate estimates of protein presence, and increase protein recall by as much as 30% in complex samples, while also increasing precision. A comprehensive suite of benchmarking datasets is introduced for evaluation in yeast. Methods to assess statistical significance in the absence of ground truth are also introduced and employed whenever applicable. This dissertation also describes a database indexing solution to improve speed and scalability of protein identification experiments. The method, MSFound, customizes a metric-space database index and its associated approximate k-nearest-neighbor search algorithm with a semi-metric distance designed to match noisy spectra. MSFound achieves an order of magnitude speedup over traditional spectra database searches while maintaining scalability.<br>text

APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Bioinformatics. Indexing"

1

Bonnici, Vincenzo, Alfredo Ferro, Rosalba Giugno, Alfredo Pulvirenti, and Dennis Shasha. "Enhancing Graph Database Indexing by Suffix Tree Structure." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16001-1_17.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Han, Fengling, Jiankun Hu, and Xinghuo Yu. "A Biometric Encryption Approach Incorporating Fingerprint Indexing in Key Generation." In Computational Intelligence and Bioinformatics. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11816102_38.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Välimäki, Niko, and Eric Rivals. "Scalable and Versatile k-mer Indexing for High-Throughput Sequencing Data." In Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38036-5_24.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Mai, Huijun, Dinghua Li, Yifan Zhang, et al. "AC-DIAMOND: Accelerating Protein Alignment via Better SIMD Parallelization and Space-Efficient Indexing." In Bioinformatics and Biomedical Engineering. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31744-1_38.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Lourenço, Anália, Sónia Carneiro, Eugénio C. Ferreira, et al. "Biomedical Text Mining Applied to Document Retrieval and Semantic Indexing." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_146.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Pareek, Rekha, and Sudhir Kumar. "Open Access Journal in Bioinformatics." In Biotechnology. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8903-7.ch063.

Full text

Abstract:

Bioinformatics is rapidly growing, interdisciplinary field of science, where methods from information technology, computer science, mathematics, and statistics are used to solve problems of biological science. To access latest scholarly articles in such an important branch one cannot deny the importance of open access journals. In this chapter an attempt has been made to access the current status of open access journals of bioinformatics which are covered by Directory of Open Access Journals (DOAJ) on various parameters like country and language of publication, their currency, impact factor, article processing charges, copyright licensing model they are using, platform for hosting and their coverage in abstracting/indexing databases.

APA, Harvard, Vancouver, ISO, and other styles

7

Pareek, Rekha, and Sudhir Kumar. "Open Access Journal in Bioinformatics." In Library and Information Services for Bioinformatics Education and Research. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1871-6.ch014.

Full text

Abstract:

Bioinformatics is rapidly growing, interdisciplinary field of science, where methods from information technology, computer science, mathematics, and statistics are used to solve problems of biological science. To access latest scholarly articles in such an important branch one cannot deny the importance of open access journals. In this chapter an attempt has been made to access the current status of open access journals of bioinformatics which are covered by Directory of Open Access Journals (DOAJ) on various parameters like country and language of publication, their currency, impact factor, article processing charges, copyright licensing model they are using, platform for hosting and their coverage in abstracting/indexing databases.

APA, Harvard, Vancouver, ISO, and other styles

8

Sidhom, Sahbi, Noureddine Bourkache, and Mourad Laghrouche. "Multimodal Indexing and Information Retrieval in Medical Image Mammographies." In Advances in Bioinformatics and Biomedical Engineering. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8811-7.ch011.

Full text

Abstract:

In this chapter, we propose a new indexing approach on medical “image scanner” databases combining the analysis process of the texture characteristics with the information contents. The proposed model is based on the digital image components using the vector of characteristics. This vector represent the morphological processing result on image texture. It is linked to semantic attributes of the image using the annotations of medical professionals. Our context of study is based on “Mammographic Image Analysis” (MIAS) in databases. The first aspect concerning the morphology processing on images called the “numerical signature” vector. In our approach, the image analysis of the texture is based on the Gabor Wavelets (or Filters) Theory. In offline processing for each image in MIAS databases, the Gabor Wavelets determine all numerical signatures: vectors of image characteristics as multi-index. In online, the query by image is in real-time processing to define the query signature (or image-query vectors) and to determine similarities by matching of multi-index with all images in databases. The similarities are built between the image-query and images in MIAS databases using the same Gabors' algorithms implemented. In order to evaluate the robustness of our system (based on multi-index, semantic attributes, query and information retrieval by image), we experiment with a controlled database of 320 mammographies. The performance results show a set of successful criteria in image representations based on the Gabor's Wavelets, semantic attributes and combining with significant ratios in the system recall and precision.

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Bioinformatics. Indexing"

1

Cho, Deil, Arfath Parsha, Shinjae Yoo, Susan E. Pepper, and Yonggang Cui. "A Survey of Logstash for Indexing Bioinformatics Data." In 2018 New York Scientific Data Summit (NYSDS). IEEE, 2018. http://dx.doi.org/10.1109/nysds.2018.8538952.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

HUANG, ZI H., XIAOFANG ZHOU, and DAWEI SONG. "HIGH DIMENSIONAL INDEXING FOR PROTEIN STRUCTURE MATCHING USING BOWTIES." In 3rd Asia-Pacific Bioinformatics Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2005. http://dx.doi.org/10.1142/9781860947322_0003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Gao, F., and M. J. Zaki. "PSIST: indexing protein structures using suffix trees." In 2005 IEEE Computational Systems Bioinformatics Conference (CSB'05). IEEE, 2005. http://dx.doi.org/10.1109/csb.2005.46.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Alatabbi, Ali, Carl Barton, and Costas S. Iliopoulos. "On the repetitive collection indexing problem." In 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2012. http://dx.doi.org/10.1109/bibmw.2012.6470220.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Claude, Francisco, Antonio Farina, Miguel A. Martínez-Prieto, and Gonzalo Navarro. "Compressed q-Gram Indexing for Highly Repetitive Biological Sequences." In 2010 IEEE International Conference on BioInformatics and BioEngineering. IEEE, 2010. http://dx.doi.org/10.1109/bibe.2010.22.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Huang, Yi, and Insu Song. "Indexing Biosignal for Integrated Health Social Networks." In ICBBE '19: 2019 6th International Conference on Biomedical and Bioinformatics Engineering. ACM, 2019. http://dx.doi.org/10.1145/3375923.3375936.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Hoksza, David. "DDPIn - Distance and density based protein indexing." In 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2009. http://dx.doi.org/10.1109/cibcb.2009.4925737.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

An, Jiye, Xudong Lu, Huilong Duan, Haomin Li, and Peipei Jia. "An Act Indexing Information Model for Clinical Data Integration." In 2007 1st International Conference on Bioinformatics and Biomedical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/icbbe.2007.284.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Gasper, William, Parvathi Chundi, and Dario Ghersi. "MeSH Indexing Using the Biomedical Citation Network." In BCB '20: 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. ACM, 2020. http://dx.doi.org/10.1145/3388440.3412466.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Yogev, Sivan, Nimrod Milo, and Michal Ziv-Ukelson. "StemSearch: RNA search tool based on stem identification and indexing." In 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2013. http://dx.doi.org/10.1109/bibm.2013.6732478.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!