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1639 result(s) for 'natural language processing' within BMC Bioinformatics

Page 31 of 33

  1. Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or vot...

    Authors: Ricardo ZN Vêncio, Leonardo Varuzza, Carlos A de B Pereira, Helena Brentani and Ilya Shmulevich
    Citation: BMC Bioinformatics 2007 8:246
  2. Molecular simulations are used to provide insight into protein structure and dynamics, and have the potential to provide important context when predicting the impact of sequence variation on protein function. ...

    Authors: Matthew D. McCoy, Vikram Shivakumar, Sridhar Nimmagadda, Mohsin Saleet Jafri and Subha Madhavan
    Citation: BMC Bioinformatics 2019 20:171
  3. Targeted next-generation sequencing is playing an increasingly important role in biological research and clinical diagnosis by allowing researchers to sequence high priority genes at much higher depths and at ...

    Authors: Likun Wang, Cong Zhang, Johnathan Watkins, Yan Jin, Michael McNutt and Yuxin Yin
    Citation: BMC Bioinformatics 2016 17:153
  4. Variations in DNA copy number have an important contribution to the development of several diseases, including autism, schizophrenia and cancer. Single-cell sequencing technology allows the dissection of genom...

    Authors: Changsheng Zhang, Hongmin Cai, Jingying Huang and Yan Song
    Citation: BMC Bioinformatics 2016 17:384
  5. With the recent proliferation of single-cell RNA-Seq experiments, several methods have been developed for unsupervised analysis of the resulting datasets. These methods often rely on unintuitive hyperparameter...

    Authors: Jesse M. Zhang, Jue Fan, H. Christina Fan, David Rosenfeld and David N. Tse
    Citation: BMC Bioinformatics 2018 19:93
  6. In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been pro...

    Authors: Koki Tsuyuzaki, Gota Morota, Manabu Ishii, Takeru Nakazato, Satoru Miyazaki and Itoshi Nikaido
    Citation: BMC Bioinformatics 2015 16:45
  7. Identifying protein complexes from protein-protein interaction (PPI) network is one of the most important tasks in proteomics. Existing computational methods try to incorporate a variety of biological evidence...

    Authors: Bo Xu, Kun Li, Wei Zheng, Xiaoxia Liu, Yijia Zhang, Zhehuan Zhao and Zengyou He
    Citation: BMC Bioinformatics 2018 19:535
  8. Humans have adapted to widespread changes during the past 2 million years in both environmental and lifestyle factors. This is evident in overall body alterations such as average height and brain size. Althoug...

    Authors: Mainá Bitar, Stefanie Kuiper, Elizabeth A. O’Brien and Guy Barry
    Citation: BMC Bioinformatics 2019 20(Suppl 9):406

    This article is part of a Supplement: Volume 20 Supplement 9

  9. High-throughput technologies have brought tremendous changes to biological domains, and the resulting high-dimensional data has also posed enormous challenges to computational science. A Bayesian network is a ...

    Authors: Jiajin Chen, Ruyang Zhang, Xuesi Dong, Lijuan Lin, Ying Zhu, Jieyu He, David C. Christiani, Yongyue Wei and Feng Chen
    Citation: BMC Bioinformatics 2019 20:711
  10. Electron tomography (ET) is an important technique for the study of complex biological structures and their functions. Electron tomography reconstructs the interior of a three-dimensional object from its proje...

    Authors: Lun Li, Renmin Han, Zhaotian Zhang, Tiande Guo, Zhiyong Liu and Fa Zhang
    Citation: BMC Bioinformatics 2020 21(Suppl 6):202

    This article is part of a Supplement: Volume 21 Supplement 6

  11. Genomic prediction is an advanced method for estimating genetic values, which has been widely accepted for genetic evaluation in animal and disease-risk prediction in human. It estimates genetic values with ge...

    Authors: Dan Jiang, Cong Xin, Jinhua Ye, Yingbo Yuan and Ming Fang
    Citation: BMC Bioinformatics 2019 20:731
  12. Although various machine learning-based predictors have been developed for estimating protein–protein interactions, their performances vary with dataset and species, and are affected by two primary aspects: ch...

    Authors: Kuan-Hsi Chen, Tsai-Feng Wang and Yuh-Jyh Hu
    Citation: BMC Bioinformatics 2019 20:308
  13. Tools for high throughput sequencing and de novo assembly make the analysis of transcriptomes (i.e. the suite of genes expressed in a tissue) feasible for almost any organism. Yet a challenge for biologists is th...

    Authors: Daniel I Speiser, M Sabrina Pankey, Alexander K Zaharoff, Barbara A Battelle, Heather D Bracken-Grissom, Jesse W Breinholt, Seth M Bybee, Thomas W Cronin, Anders Garm, Annie R Lindgren, Nipam H Patel, Megan L Porter, Meredith E Protas, Ajna S Rivera, Jeanne M Serb, Kirk S Zigler…
    Citation: BMC Bioinformatics 2014 15:350
  14. In the post-genomic era, transcriptomics and proteomics provide important information to understand the genomes. With fast development of high-throughput technology, more and more transcriptomics and proteomic...

    Authors: Guangyong Zheng, Haibo Wang, Chaochun Wei and Yixue Li
    Citation: BMC Bioinformatics 2011 12(Suppl 14):S6

    This article is part of a Supplement: Volume 12 Supplement 14

  15. Several methods have been developed to predict the pathogenicity of missense mutations but none has been specifically designed for classification of variants in mtDNA-encoded polypeptides. Moreover, there is n...

    Authors: Antonio Martín-Navarro, Andrés Gaudioso-Simón, Jorge Álvarez-Jarreta, Julio Montoya, Elvira Mayordomo and Eduardo Ruiz-Pesini
    Citation: BMC Bioinformatics 2017 18:158
  16. Genome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than repres...

    Authors: Toshiyuki T. Yokoyama, Yoshitaka Sakamoto, Masahide Seki, Yutaka Suzuki and Masahiro Kasahara
    Citation: BMC Bioinformatics 2019 20:548
  17. Development of a fast and accurate scoring function in virtual screening remains a hot issue in current computer-aided drug research. Different scoring functions focus on diverse aspects of ligand binding, and...

    Authors: Honglin Li, Hailei Zhang, Mingyue Zheng, Jie Luo, Ling Kang, Xiaofeng Liu, Xicheng Wang and Hualiang Jiang
    Citation: BMC Bioinformatics 2009 10:58
  18. Obesity is a complex disorder associated with an increased risk of developing several comorbid chronic diseases, including postmenopausal breast cancer. Although many studies have investigated this issue, the ...

    Authors: Ilaria Granata, Enrico Troiano, Mara Sangiovanni and Mario Rosario Guarracino
    Citation: BMC Bioinformatics 2019 20(Suppl 4):162

    This article is part of a Supplement: Volume 20 Supplement 4

  19. The construction of the Disease Ontology (DO) has helped promote the investigation of diseases and disease risk factors. DO enables researchers to analyse disease similarity by adopting semantic similarity mea...

    Authors: Jiang Li, Binsheng Gong, Xi Chen, Tao Liu, Chao Wu, Fan Zhang, Chunquan Li, Xiang Li, Shaoqi Rao and Xia Li
    Citation: BMC Bioinformatics 2011 12:266
  20. Third-generation sequencing platforms, such as PacBio sequencing, have been developed rapidly in recent years. PacBio sequencing generates much longer reads than the second-generation sequencing (or the next g...

    Authors: Wenmin Zhang, Ben Jia and Chaochun Wei
    Citation: BMC Bioinformatics 2019 20:352
  21. Contemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon tha...

    Authors: Markos Antonopoulos, Dimitra Dionysiou, Georgios Stamatakos and Nikolaos Uzunoglu
    Citation: BMC Bioinformatics 2019 20:442

    The Publisher Correction to this article has been published in BMC Bioinformatics 2019 20:500

  22. Helitron is a rolling-circle DNA transposon; it plays an important role in plant evolution. However, Helitron distribution and contribution to evolution at the family level have not been previously investigated.

    Authors: Kaining Hu, Kai Xu, Jing Wen, Bin Yi, Jinxiong Shen, Chaozhi Ma, Tingdong Fu, Yidan Ouyang and Jinxing Tu
    Citation: BMC Bioinformatics 2019 20:354
  23. Intronless genes are a significant characteristic of prokaryotes. Systematic identification and annotation are primary and crucial steps for determining the functions of intronless genes and understanding thei...

    Authors: Hanwei Yan, Xiaogang Dai, Kai Feng, Qiuyue Ma and Tongming Yin
    Citation: BMC Bioinformatics 2016 17:289
  24. Codon bias is believed to play an important role in the control of gene expression. In Escherichia coli, some rare codons, which can limit the expression level of exogenous protein, have been defined by gene engi...

    Authors: Xianming Wu, Songfeng Wu, Dong Li, Jiyang Zhang, Lin Hou, Jie Ma, Wanlin Liu, Daming Ren, Yunping Zhu and Fuchu He
    Citation: BMC Bioinformatics 2010 11:61
  25. Genome-wide Association Studies (GWAS) have contributed to unraveling associations between genetic variants in the human genome and complex traits for more than a decade. While many works have been invented as...

    Authors: Haohan Wang, Tianwei Yue, Jingkang Yang, Wei Wu and Eric P. Xing
    Citation: BMC Bioinformatics 2019 20(Suppl 23):656

    This article is part of a Supplement: Volume 20 Supplement 23

  26. De novo genome assembly of next-generation sequencing data is one of the most important current problems in bioinformatics, essential in many biological applications. In spite of significant amount of work in ...

    Authors: Lucian Ilie, Bahlul Haider, Michael Molnar and Roberto Solis-Oba
    Citation: BMC Bioinformatics 2014 15:302
  27. The pan-genome of a bacterial species consists of a core and an accessory gene pool. The accessory genome is thought to be an important source of genetic variability in bacterial populations and is gained thro...

    Authors: Chad Laing, Cody Buchanan, Eduardo N Taboada, Yongxiang Zhang, Andrew Kropinski, Andre Villegas, James E Thomas and Victor PJ Gannon
    Citation: BMC Bioinformatics 2010 11:461
  28. Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working...

    Authors: Edison Ong, Jiangan Xie, Zhaohui Ni, Qingping Liu, Sirarat Sarntivijai, Yu Lin, Daniel Cooper, Raymond Terryn, Vasileios Stathias, Caty Chung, Stephan Schürer and Yongqun He
    Citation: BMC Bioinformatics 2017 18(Suppl 17):556

    This article is part of a Supplement: Volume 18 Supplement 17

  29. Biological interpretation of gene/protein lists resulting from -omics experiments can be a complex task. A common approach consists of reviewing Gene Ontology (GO) annotations for entries in such lists and sea...

    Authors: Mikhail Pomaznoy, Brendan Ha and Bjoern Peters
    Citation: BMC Bioinformatics 2018 19:470
  30. RIFINs and STEVORs are variant surface antigens expressed by P. falciparum that play roles in severe malaria pathogenesis and immune evasion. These two highly diverse multigene families feature multiple paralogs,...

    Authors: Albert E. Zhou, Zalak V. Shah, Katie R. Bradwell, James B. Munro, Andrea A. Berry, David Serre, Shannon Takala-Harrison, Timothy D. O’Connor, Joana C. Silva and Mark A. Travassos
    Citation: BMC Bioinformatics 2022 23:15
  31. Profile Hidden Markov Models (pHMMs) are a widely used tool for protein family research. Up to now, however, there exists no method to visualize all of their central aspects graphically in an intuitively under...

    Authors: Benjamin Schuster-Böckler, Jörg Schultz and Sven Rahmann
    Citation: BMC Bioinformatics 2004 5:7
  32. Because of the short read length of high throughput sequencing data, assembly errors are introduced in genome assembly, which may have adverse impact to the downstream data analysis. Several tools have been de...

    Authors: Xiao Zhu, Henry C. M. Leung, Rongjie Wang, Francis Y. L. Chin, Siu Ming Yiu, Guangri Quan, Yajie Li, Rui Zhang, Qinghua Jiang, Bo Liu, Yucui Dong, Guohui Zhou and Yadong Wang
    Citation: BMC Bioinformatics 2015 16:386
  33. Much effort is currently made to develop the Gene Ontology (GO). Due to the dynamic nature of information it addresses, GO undergoes constant updates whose results are released at regular intervals as separate...

    Authors: Jong C Park, Tak-eun Kim and Jinah Park
    Citation: BMC Bioinformatics 2008 9(Suppl 3):S7

    This article is part of a Supplement: Volume 9 Supplement 3

  34. Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of ...

    Authors: Wei Dong, Litao Yang, Kailin Shen, Banghyun Kim, Gijs A Kleter, Hans JP Marvin, Rong Guo, Wanqi Liang and Dabing Zhang
    Citation: BMC Bioinformatics 2008 9:260
  35. Many high throughput sequencing (HTS) approaches, such as the Roche/454 platform, produce sequences in which the quality of the sequence (as measured by a Phred-like quality scores) decreases linearly across a...

    Authors: Ram Krishna Shrestha, Baruch Lubinsky, Vijay B Bansode, Mónica BJ Moinz, Grace P McCormack and Simon A Travers
    Citation: BMC Bioinformatics 2014 15:33

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