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Knowledge-based analysis

Section edited by Hagit Shatkay

This section incorporates all aspects of knowledge-based analysis in biology including but not limited to: methods for the processing of text, ontologies and other computational representations of biological knowledge, as well as applications of knowledge-based systems for gaining insight into biology and biological data.

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  1. In this study, we compared four models for predicting rice blast disease, two operational process-based models (Yoshino and Water Accounting Rice Model (WARM)) and two approaches based on machine learning algo...

    Authors: David F. Nettleton, Dimitrios Katsantonis, Argyris Kalaitzidis, Natasa Sarafijanovic-Djukic, Pau Puigdollers and Roberto Confalonieri

    Citation: BMC Bioinformatics 2019 20:514

    Content type: Research article

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  2. Although a few comparison methods based on the biological meaning of gene lists have been developed, the goProfiles approach is one of the few that are being used for that purpose. It consists of projecting li...

    Authors: Alex Sánchez-Pla, Miquel Salicrú and Jordi Ocaña

    Citation: BMC Bioinformatics 2019 20:441

    Content type: Methodology article

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  3. Background Consisting of dictated free-text documents such as discharge summaries, medical narratives are widely used in medical natural language processing. Relationships between anatomical entities and human...

    Authors: Yipei Wang, Xingyu Fan, Luoxin Chen, Eric I-Chao Chang, Sophia Ananiadou, Junichi Tsujii and Yan Xu

    Citation: BMC Bioinformatics 2019 20:430

    Content type: Methodology article

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  4. Diagnosis and treatment decisions in cancer increasingly depend on a detailed analysis of the mutational status of a patient’s genome. This analysis relies on previously published information regarding the ass...

    Authors: Jurica Ševa, David Luis Wiegandt, Julian Götze, Mario Lamping, Damian Rieke, Reinhold Schäfer, Patrick Jähnichen, Madeleine Kittner, Steffen Pallarz, Johannes Starlinger, Ulrich Keilholz and Ulf Leser

    Citation: BMC Bioinformatics 2019 20:429

    Content type: Research article

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  5. RNA molecules play many crucial roles in living systems. The spatial complexity that exists in RNA structures determines their cellular functions. Therefore, understanding RNA folding conformations, in particu...

    Authors: Congzhe Su, Jeffery D. Weir, Fei Zhang, Hao Yan and Teresa Wu

    Citation: BMC Bioinformatics 2019 20:373

    Content type: Research article

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  6. In the era of precision oncology and publicly available datasets, the amount of information available for each patient case has dramatically increased. From clinical variables and PET-CT radiomics measures to ...

    Authors: Michael C. Rendleman, John M. Buatti, Terry A. Braun, Brian J. Smith, Chibuzo Nwakama, Reinhard R. Beichel, Bart Brown and Thomas L. Casavant

    Citation: BMC Bioinformatics 2019 20:339

    Content type: Research article

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  7. Ontology has attracted substantial attention from both academia and industry. Handling uncertainty reasoning is important in researching ontology. For example, when a patient is suffering from cirrhosis, the a...

    Authors: Ying Shen, Yaliang Li, Hai-Tao Zheng, Buzhou Tang and Min Yang

    Citation: BMC Bioinformatics 2019 20:330

    Content type: Research article

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  8. The retrieval of plant-related information is a challenging task due to variations in species name mentions as well as spelling or typographical errors across data sources. Scalable solutions are needed for id...

    Authors: Vivekanand Sharma, Maria Isabel Restrepo and Indra Neil Sarkar

    Citation: BMC Bioinformatics 2019 20:263

    Content type: Software

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  9. Set enrichment methods are commonly used to analyze high-dimensional molecular data and gain biological insight into molecular or clinical phenotypes. One important category of analysis methods employs an enri...

    Authors: Joanna Roder, Benjamin Linstid and Carlos Oliveira

    Citation: BMC Bioinformatics 2019 20:257

    Content type: Methodology article

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  10. With advancements in high-throughput technologies, the cost of obtaining expression profiles of both mRNA and microRNA in the same individual has substantially decreased. Integrated analysis of these profiles ...

    Authors: Ti-Tai Wang, Chien-Yueh Lee, Liang-Chuan Lai, Mong-Hsun Tsai, Tzu-Pin Lu and Eric Y. Chuang

    Citation: BMC Bioinformatics 2019 20:239

    Content type: Software

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  11. Neural network based embedding models are receiving significant attention in the field of natural language processing due to their capability to effectively capture semantic information representing words, sen...

    Authors: Kathrin Blagec, Hong Xu, Asan Agibetov and Matthias Samwald

    Citation: BMC Bioinformatics 2019 20:178

    Content type: Research article

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  12. For large international research consortia, such as those funded by the European Union’s Horizon 2020 programme or the Innovative Medicines Initiative, good data coordination practices and tools are essential ...

    Authors: Wei Gu, Reha Yildirimman, Emmanuel Van der Stuyft, Denny Verbeeck, Sascha Herzinger, Venkata Satagopam, Adriano Barbosa-Silva, Reinhard Schneider, Bodo Lange, Hans Lehrach, Yike Guo, David Henderson and Anthony Rowe

    Citation: BMC Bioinformatics 2019 20:164

    Content type: Methodology article

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  13. Biological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data access...

    Authors: Daniel Perez-Gil, Francisco J. Lopez, Joaquin Dopazo, Pablo Marin-Garcia, Augusto Rendon and Ignacio Medina

    Citation: BMC Bioinformatics 2019 20:159

    Content type: Software

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  14. Functional annotation of genes is an essential step in omics data analysis. Multiple databases and methods are currently available to summarize the functions of sets of genes into higher level representations,...

    Authors: Giovanni Scala, Angela Serra, Veer Singh Marwah, Laura Aliisa Saarimäki and Dario Greco

    Citation: BMC Bioinformatics 2019 20:79

    Content type: Software

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  15. Understanding the genetic networks and their role in chronic diseases (e.g., cancer) is one of the important objectives of biological researchers. In this work, we present a text mining system that constructs ...

    Authors: Amira Al-Aamri, Kamal Taha, Yousof Al-Hammadi, Maher Maalouf and Dirar Homouz

    Citation: BMC Bioinformatics 2019 20:70

    Content type: Methodology article

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  16. Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In ...

    Authors: Imane Boudellioua, Maxat Kulmanov, Paul N. Schofield, Georgios V. Gkoutos and Robert Hoehndorf

    Citation: BMC Bioinformatics 2019 20:65

    Content type: Software

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  17. Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and de...

    Authors: Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du, Jian Chen and Jinzhun Wu

    Citation: BMC Bioinformatics 2019 20:62

    Content type: Research article

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  18. Accurate prediction of anticancer drug responses in cell lines is a crucial step to accomplish the precision medicine in oncology. Although many popular computational models have been proposed towards this non...

    Authors: Dong Wei, Chuanying Liu, Xiaoqi Zheng and Yushuang Li

    Citation: BMC Bioinformatics 2019 20:44

    Content type: Research article

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  19. Recent studies have proposed deep learning techniques, namely recurrent neural networks, to improve biomedical text mining tasks. However, these techniques rarely take advantage of existing domain-specific res...

    Authors: Andre Lamurias, Diana Sousa, Luka A. Clarke and Francisco M. Couto

    Citation: BMC Bioinformatics 2019 20:10

    Content type: Research article

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  20. The development of high-throughput sequencing and analysis has accelerated multi-omics studies of thousands of microbial species, metagenomes, and infectious disease pathogens. Omics studies are enabling genot...

    Authors: Indresh Singh, Mehmet Kuscuoglu, Derek M. Harkins, Granger Sutton, Derrick E. Fouts and Karen E. Nelson

    Citation: BMC Bioinformatics 2019 20:8

    Content type: Software

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  21. Biomedical knowledge grows in complexity, and becomes encoded in network-based repositories, which include focused, expert-drawn diagrams, networks of evidence-based associations and established ontologies. Co...

    Authors: Marek Ostaszewski, Emmanuel Kieffer, Grégoire Danoy, Reinhard Schneider and Pascal Bouvry

    Citation: BMC Bioinformatics 2018 19:308

    Content type: Research article

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  22. Public biomedical data repositories often provide web-based interfaces to collect experimental metadata. However, these interfaces typically reflect the ad hoc metadata specification practices of the associate...

    Authors: Syed Ahmad Chan Bukhari, Marcos Martínez-Romero, Martin J. O’ Connor, Attila L. Egyedi, Debra Willrett, John Graybeal, Mark A. Musen, Kei-Hoi Cheung and Steven H. Kleinstein

    Citation: BMC Bioinformatics 2018 19:268

    Content type: Software

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  23. For automated reading of scientific publications to extract useful information about molecular mechanisms it is critical that genes, proteins and other entities be correctly associated with uniform identifiers...

    Authors: John A. Bachman, Benjamin M. Gyori and Peter K. Sorger

    Citation: BMC Bioinformatics 2018 19:248

    Content type: Database

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  24. Asthma and allergies prevalence increased in recent decades, being a serious global health problem. They are complex diseases with strong contextual influence, so that the use of advanced machine learning tool...

    Authors: Rafael V. Veiga, Helio J. C. Barbosa, Heder S. Bernardino, João M. Freitas, Caroline A. Feitosa, Sheila M. A. Matos, Neuza M. Alcântara-Neves and Maurício L. Barreto

    Citation: BMC Bioinformatics 2018 19:245

    Content type: Methodology article

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  25. Identifying protein functional sites (PFSs) and, particularly, the physicochemical interactions at these sites is critical to understanding protein functions and the biochemical reactions involved. Several kno...

    Authors: Min Han, Yifan Song, Jiaqiang Qian and Dengming Ming

    Citation: BMC Bioinformatics 2018 19:204

    Content type: Research article

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  26. Predicting a list of plant taxa most likely to be observed at a given geographical location and time is useful for many scenarios in biodiversity informatics. Since efficient plant species identification is im...

    Authors: Hans Christian Wittich, Marco Seeland, Jana Wäldchen, Michael Rzanny and Patrick Mäder

    Citation: BMC Bioinformatics 2018 19:190

    Content type: Research article

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  27. A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditio...

    Authors: Gurnoor Singh, Arnold Kuzniar, Erik M. van Mulligen, Anand Gavai, Christian W. Bachem, Richard G.F. Visser and Richard Finkers

    Citation: BMC Bioinformatics 2018 19:183

    Content type: Software

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  28. Comparing and classifying functions of gene products are important in today’s biomedical research. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most wi...

    Authors: Jiongmin Zhang, Ke Jia, Jinmeng Jia and Ying Qian

    Citation: BMC Bioinformatics 2018 19:161

    Content type: Methodology article

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  29. Recent cancer genome studies on many human cancer types have relied on multiple molecular high-throughput technologies. Given the vast amount of data that has been generated, there are surprisingly few databas...

    Authors: Rasmus Krempel, Pranav Kulkarni, Annie Yim, Ulrich Lang, Bianca Habermann and Peter Frommolt

    Citation: BMC Bioinformatics 2018 19:156

    Content type: Research article

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  30. Mutations in the FMS-like tyrosine kinase 3 (FLT3) are associated with uncontrolled cellular functions that contribute to the development of acute myeloid leukaemia (AML). We performed computer simulations of ...

    Authors: Antoine Buetti-Dinh and Ran Friedman

    Citation: BMC Bioinformatics 2018 19:155

    Content type: Research article

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  31. Drug repositioning is the process of identifying new targets for known drugs. It can be used to overcome problems associated with traditional drug discovery by adapting existing drugs to treat new discovered d...

    Authors: Makbule Guclin Ozsoy, Tansel Özyer, Faruk Polat and Reda Alhajj

    Citation: BMC Bioinformatics 2018 19:136

    Content type: Research article

    Published on:

    The Correction to this article has been published in BMC Bioinformatics 2018 19:250

  32. Drug repositioning is the process of identifying new uses for existing drugs. Computational drug repositioning methods can reduce the time, costs and risks of drug development by automating the analysis of the...

    Authors: Pathima Nusrath Hameed, Karin Verspoor, Snezana Kusljic and Saman Halgamuge

    Citation: BMC Bioinformatics 2018 19:129

    Content type: Research article

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  33. Patient background (e.g. age, sex, and primary disease) is an important factor to consider when monitoring adverse drug events (ADEs) for the purpose of pharmacovigilance. However, in disproportionality method...

    Authors: Yoshihiro Noguchi, Anri Ueno, Manami Otsubo, Hayato Katsuno, Ikuto Sugita, Yuta Kanematsu, Aki Yoshida, Hiroki Esaki, Tomoya Tachi and Hitomi Teramachi

    Citation: BMC Bioinformatics 2018 19:124

    Content type: Research article

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  34. Consumers increasingly use online resources for their health information needs. While current search engines can address these needs to some extent, they generally do not take into account that most health inf...

    Authors: Halil Kilicoglu, Asma Ben Abacha, Yassine Mrabet, Sonya E. Shooshan, Laritza Rodriguez, Kate Masterton and Dina Demner-Fushman

    Citation: BMC Bioinformatics 2018 19:34

    Content type: Research Article

    Published on:

2018 Journal Metrics

  • Citation Impact
    2.511 - 2-year Impact Factor
    2.970 - 5-year Impact Factor
    0.855 - Source Normalized Impact per Paper (SNIP)
    1.374 - SCImago Journal Rank (SJR)

    Usage 
    4,129,368 downloads

    Social Media Impact
    4446 mentions

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