Skip to content

Advertisement

Sequence analysis (applications)

Section edited by João Setubal

This section incorporates all aspects of sequence analysis applications, including but not limited to: software, workflows and webservers dealing with applied sequence/genome analysis, sequence assembly, analysis of sequence features, and protein function and ligand binding, estimated through sequence features.

Page 1 of 24
  1. Content type: Software

    Large sequence datasets are difficult to visualize and handle. Additionally, they often do not represent a random subset of the natural diversity, but the result of uncoordinated and convenience sampling. Cons...

    Authors: Fabrizio Menardo, Chloé Loiseau, Daniela Brites, Mireia Coscolla, Sebastian M. Gygli, Liliana K. Rutaihwa, Andrej Trauner, Christian Beisel, Sonia Borrell and Sebastien Gagneux

    Citation: BMC Bioinformatics 2018 19:164

    Published on:

  2. Content type: Research article

    In the last decade and a half it has been firmly established that a large number of proteins do not adopt a well-defined (ordered) structure under physiological conditions. Such intrinsically disordered protei...

    Authors: Nenad S. Mitić, Saša N. Malkov, Jovana J. Kovačević, Gordana M. Pavlović-Lažetić and Miloš V. Beljanski

    Citation: BMC Bioinformatics 2018 19:158

    Published on:

  3. Content type: Database

    Bioactive peptides, including biological sources-derived peptides with different biological activities, are protein fragments that influence the functions or conditions of organisms, in particular humans and a...

    Authors: Krittima Anekthanakul, Apiradee Hongsthong, Jittisak Senachak and Marasri Ruengjitchatchawalya

    Citation: BMC Bioinformatics 2018 19:149

    Published on:

  4. Content type: Software

    The study of the huge diversity of immune receptors, often referred to as immune repertoire profiling, is a prerequisite for diagnosis, prognostication and monitoring of hematological disorders. In the era of ...

    Authors: Christos Maramis, Athanasios Gkoufas, Anna Vardi, Evangelia Stalika, Kostas Stamatopoulos, Anastasia Hatzidimitriou, Nicos Maglaveras and Ioanna Chouvarda

    Citation: BMC Bioinformatics 2018 19:144

    Published on:

  5. Content type: Research article

    After decades of identifying risk factors using array-based genome-wide association studies (GWAS), genetic research of complex diseases has shifted to sequencing-based rare variants discovery. This requires l...

    Authors: Yingxue Ren, Joseph S. Reddy, Cyril Pottier, Vivekananda Sarangi, Shulan Tian, Jason P. Sinnwell, Shannon K. McDonnell, Joanna M. Biernacka, Minerva M. Carrasquillo, Owen A. Ross, Nilüfer Ertekin-Taner, Rosa Rademakers, Matthew Hudson, Liudmila Sergeevna Mainzer and Yan W. Asmann

    Citation: BMC Bioinformatics 2018 19:139

    Published on:

  6. Content type: Research article

    Single nucleotide polymorphisms (SNPs) located within the human genome have been shown to have utility as markers of identity in the differentiation of DNA from individual contributors. Massively parallel DNA ...

    Authors: M. Heath Farris, Andrew R. Scott, Pamela A. Texter, Marta Bartlett, Patricia Coleman and David Masters

    Citation: BMC Bioinformatics 2018 19:126

    Published on:

  7. Content type: Methodology article

    High quality functional annotation is essential for understanding the phenotypic consequences encoded in a genome. Despite improvements in bioinformatics methods, millions of sequences in databanks are not ass...

    Authors: Jonathan Mercier, Adrien Josso, Claudine Médigue and David Vallenet

    Citation: BMC Bioinformatics 2018 19:132

    Published on:

  8. Content type: Methodology Article

    Genome-wide association studies (GWASs) have been widely used to discover the genetic basis of complex phenotypes. However, standard single-SNP GWASs suffer from lack of power. In particular, they do not direc...

    Authors: Christine Sinoquet

    Citation: BMC Bioinformatics 2018 19:106

    Published on:

  9. Content type: Software

    Quantitative trait locus (QTL) mapping in genetic data often involves analysis of correlated observations, which need to be accounted for to avoid false association signals. This is commonly performed by model...

    Authors: Andrey Ziyatdinov, Miquel Vázquez-Santiago, Helena Brunel, Angel Martinez-Perez, Hugues Aschard and Jose Manuel Soria

    Citation: BMC Bioinformatics 2018 19:68

    Published on:

  10. Content type: Software

    Small RNA molecules play important roles in many biological processes and their dysregulation or dysfunction can cause disease. The current method of choice for genome-wide sRNA expression profiling is deep se...

    Authors: Raza-Ur Rahman, Abhivyakti Gautam, Jörn Bethune, Abdul Sattar, Maksims Fiosins, Daniel Sumner Magruder, Vincenzo Capece, Orr Shomroni and Stefan Bonn

    Citation: BMC Bioinformatics 2018 19:54

    Published on:

  11. Content type: Research Article

    The ease at which influenza virus sequence data can be used to estimate antigenic relationships between strains and the existence of databases containing sequence data for hundreds of thousands influenza strai...

    Authors: Christopher S. Anderson, Patrick R. McCall, Harry A. Stern, Hongmei Yang and David J. Topham

    Citation: BMC Bioinformatics 2018 19:51

    Published on:

  12. Content type: Software

    The advent of modern high-throughput genetics continually broadens the gap between the rising volume of sequencing data, and the tools required to process them. The need to pinpoint a small subset of functiona...

    Authors: Monika Mozere, Mehmet Tekman, Jameela Kari, Detlef Bockenhauer, Robert Kleta and Horia Stanescu

    Citation: BMC Bioinformatics 2018 19:46

    Published on:

  13. Content type: Research Article

    The clinical sequencing of cancer genomes to personalize therapy is becoming routine across the world. However, concerns over patient re-identification from these data lead to questions about how tightly acces...

    Authors: Dorota H. Sendorek, Cristian Caloian, Kyle Ellrott, J. Christopher Bare, Takafumi N. Yamaguchi, Adam D. Ewing, Kathleen E. Houlahan, Thea C. Norman, Adam A. Margolin, Joshua M. Stuart and Paul C. Boutros

    Citation: BMC Bioinformatics 2018 19:28

    Published on:

  14. Content type: Methodology Article

    Protein or nucleic acid sequences contain a multitude of associated annotations representing continuous sequence elements (CSEs). Comparing these CSEs is needed, whenever we want to match identical annotations...

    Authors: Roman Prytuliak, Friedhelm Pfeiffer and Bianca Hermine Habermann

    Citation: BMC Bioinformatics 2018 19:24

    Published on:

  15. Content type: Software

    Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results ...

    Authors: Jordi Martorell-Marugan, Daniel Toro-Dominguez, Marta E. Alarcon-Riquelme and Pedro Carmona-Saez

    Citation: BMC Bioinformatics 2017 18:563

    Published on:

  16. Content type: Software

    High throughput sequencing requires bioinformatics pipelines to process large volumes of data into meaningful variants that can be translated into a clinical report. These pipelines often suffer from a number ...

    Authors: Kenneth D. Doig, Jason Ellul, Andrew Fellowes, Ella R. Thompson, Georgina Ryland, Piers Blombery, Anthony T. Papenfuss and Stephen B. Fox

    Citation: BMC Bioinformatics 2017 18:555

    Published on:

  17. Content type: Software

    Haloplex targeted resequencing is a popular method to analyze both germline and somatic variants in gene panels. However, involved wet-lab procedures may introduce false positives that need to be considered in...

    Authors: Matthias Beyens, Nele Boeckx, Guy Van Camp, Ken Op de Beeck and Geert Vandeweyer

    Citation: BMC Bioinformatics 2017 18:554

    Published on:

Page 1 of 24

2016 Journal Metrics

  • Citation Impact
    2.448 - 2-year Impact Factor
    3.450 - 5-year Impact Factor
    0.946 - Source Normalized Impact per Paper (SNIP)
    1.467 - SCImago Journal Rank (SJR)

    Usage 
    3784657 downloads
    1405 Usage Factor


    Social Media Impact
    816 mentions

Advertisement