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Results and data

This section incorporates novel results, useful tools, and methods using bioinformatics in new ways, including but not limited to: biological conclusions that are only supported by bioinformatics analyses.

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  1. Current high-throughput technologies—i.e. whole genome sequencing, RNA-Seq, ChIP-Seq, etc.—generate huge amounts of data and their usage gets more widespread with each passing year. Complex analysis pipelines ...

    Authors: Daniele Dall’Olio, Nico Curti, Eugenio Fonzi, Claudia Sala, Daniel Remondini, Gastone Castellani and Enrico Giampieri

    Citation: BMC Bioinformatics 2021 22:60

    Content type: Research article

    Published on:

  2. The development of genetically modified crops (GM) includes the discovery of candidate genes through bioinformatics analysis using genomics data, gene expression, and others. Proteins of unknown function (PUFs...

    Authors: Marcos José Andrade Viana, Adhemar Zerlotini and Mauricio de Alvarenga Mudadu

    Citation: BMC Bioinformatics 2021 22:46

    Content type: Database

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  4. Biomedical research projects deal with data management requirements from multiple sources like funding agencies’ guidelines, publisher policies, discipline best practices, and their own users’ needs. We descri...

    Authors: M. Suhr, C. Lehmann, C. R. Bauer, T. Bender, C. Knopp, L. Freckmann, B. Öst Hansen, C. Henke, G. Aschenbrandt, L. K. Kühlborn, S. Rheinländer, L. Weber, B. Marzec, M. Hellkamp, P. Wieder, U. Sax…

    Citation: BMC Bioinformatics 2020 21:582

    Content type: Software

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  5. A low replication rate has been reported in some scientific areas motivating the creation of resource intensive collaborations to estimate the replication rate by repeating individual studies. The substantial ...

    Authors: L. M. Hall and A. E. Hendricks

    Citation: BMC Bioinformatics 2020 21:564

    Content type: Research article

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  6. Data handling in clinical bioinformatics is often inadequate. No freely available tools provide straightforward approaches for consistent, flexible metadata collection and linkage of related experimental data ...

    Authors: Bo Zhao, Luke Bryant, Rebecca Cordell, Michael Wilde, Dahlia Salman, Dorota Ruszkiewicz, Wadah Ibrahim, Amisha Singapuri, Tim Coats, Erol Gaillard, Caroline Beardsmore, Toru Suzuki, Leong Ng, Neil Greening, Paul Thomas, Paul Monks…

    Citation: BMC Bioinformatics 2020 21:556

    Content type: Software

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  7. The spread of infectious diseases is so important that changes the demography of the population. Therefore, prevention and intervention measures are essential to control and eliminate the disease. Among the dr...

    Authors: Mahmood Parsamanesh, Majid Erfanian and Saeed Mehrshad

    Citation: BMC Bioinformatics 2020 21:525

    Content type: Research article

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  8. DNBSEQ™ platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology. Use of data generated from DNBSEQ™ platforms to detect single nucleotide variants (SNVs) and small inse...

    Authors: Junhua Rao, Lihua Peng, Xinming Liang, Hui Jiang, Chunyu Geng, Xia Zhao, Xin Liu, Guangyi Fan, Fang Chen and Feng Mu

    Citation: BMC Bioinformatics 2020 21:518

    Content type: Research article

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  9. Any two unrelated people differ by about 20,000 missense mutations (also referred to as SAVs: Single Amino acid Variants or missense SNV). Many SAVs have been predicted to strongly affect molecular protein fun...

    Authors: Jiajun Qiu, Dmitrii Nechaev and Burkhard Rost

    Citation: BMC Bioinformatics 2020 21:452

    Content type: Research article

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  11. Quantitative polymerase chain reaction (qPCR) is the technique of choice for quantifying gene expression. While the technique itself is well established, approaches for the analysis of qPCR data continue to im...

    Authors: Michael T. Ganger, Geoffrey D. Dietz, Patrick Headley and Sarah J. Ewing

    Citation: BMC Bioinformatics 2020 21:423

    Content type: Methodology article

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  12. Two-dimensional gel electrophoresis (2-DGE) is a commonly used tool for proteomic analysis. This gel-based technique separates proteins in a sample according to their isoelectric point and molecular weight. 2-...

    Authors: Manuel Mauricio Goez, Maria C. Torres-Madronero, Sarah Rothlisberger and Edilson Delgado-Trejos

    Citation: BMC Bioinformatics 2020 21:376

    Content type: Methodology article

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  13. Well-characterized biomaterials of high quality have great potential for acceleration and quality improvement in translational biomedical research. To improve accessibility of local sample collections, efforts...

    Authors: Stephanie Heinen, Nick Schulze, Bernd Franke, Florian Klein, Clara Lehmann, Maria J. G. T. Vehreschild, Claas Gloistein, Melanie Stecher and Jörg Janne Vehreschild

    Citation: BMC Bioinformatics 2020 21:290

    Content type: Software

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  15. High-throughput technologies enable the cost-effective collection and analysis of DNA methylation data throughout the human genome. This naturally entails missing values management that can complicate the anal...

    Authors: Pietro Di Lena, Claudia Sala, Andrea Prodi and Christine Nardini

    Citation: BMC Bioinformatics 2020 21:268

    Content type: Research article

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  16. Mutations arise in the human genome in two major settings: the germline and the soma. These settings involve different inheritance patterns, time scales, chromatin structures, and environmental exposures, all ...

    Authors: William Meyerson, John Leisman, Fabio C. P. Navarro and Mark Gerstein

    Citation: BMC Bioinformatics 2020 21:227

    Content type: Research article

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  17. Currently, formal mechanisms for bioinformatics support are limited. The H3Africa Bioinformatics Network has implemented a public and freely available Helpdesk (HD), which provides generic bioinformatics suppo...

    Authors: Judit Kumuthini, Lyndon Zass, Sumir Panji, Samson P. Salifu, Jonathan K. Kayondo, Victoria Nembaware, Mamana Mbiyavanga, Ajayi Olabode, Ali Kishk, Gordon Wells and Nicola J. Mulder

    Citation: BMC Bioinformatics 2019 20:741

    Content type: Research article

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  18. Transcriptome analysis aims at gaining insight into cellular processes through discovering gene expression patterns across various experimental conditions. Biclustering is a standard approach to discover genes su...

    Authors: Vincent Branders, Pierre Schaus and Pierre Dupont

    Citation: BMC Bioinformatics 2019 20:625

    Content type: Research Article

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  19. Cancer arises through accumulation of somatically acquired genetic mutations. An important question is to delineate the temporal order of somatic mutations during carcinogenesis, which contributes to better un...

    Authors: Menghan Wang, Tianxin Yu, Jinpeng Liu, Li Chen, Arnold J. Stromberg, John L. Villano, Susanne M. Arnold, Chunming Liu and Chi Wang

    Citation: BMC Bioinformatics 2019 20:620

    Content type: Methodology Article

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  20. Lung cancer is one of the most common types of cancer, among which lung adenocarcinoma accounts for the largest proportion. Currently, accurate staging is a prerequisite for effective diagnosis and treatment o...

    Authors: Yunyun Dong, Wenkai Yang, Jiawen Wang, Juanjuan Zhao, Yan Qiang, Zijuan Zhao, Ntikurako Guy Fernand Kazihise, Yanfen Cui, Xiaotong Yang and Siyuan Liu

    Citation: BMC Bioinformatics 2019 20:578

    Content type: Research article

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  22. In biological experiments, comprehensive experimental metadata tracking – which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies – remains a challen...

    Authors: Elmar Bucher, Cheryl J. Claunch, Derrick Hee, Rebecca L. Smith, Kaylyn Devlin, Wallace Thompson, James E. Korkola and Laura M. Heiser

    Citation: BMC Bioinformatics 2019 20:542

    Content type: Software

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  23. LC-MS technology makes it possible to measure the relative abundance of numerous molecular features of a sample in single analysis. However, especially non-targeted metabolite profiling approaches generate vas...

    Authors: Marietta Kokla, Jyrki Virtanen, Marjukka Kolehmainen, Jussi Paananen and Kati Hanhineva

    Citation: BMC Bioinformatics 2019 20:492

    Content type: Research article

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  24. As genome sequencing projects grow rapidly, the diversity of organisms with recently assembled genome sequences peaks at an unprecedented scale, thereby highlighting the need to make gene functional annotation...

    Authors: Fernando Cruz, Davide Lagoa, João Mendes, Isabel Rocha, Eugénio C. Ferreira, Miguel Rocha and Oscar Dias

    Citation: BMC Bioinformatics 2019 20:454

    Content type: Methodology article

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  25. Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, ext...

    Authors: Rebecca C. Jackson, James P. Balhoff, Eric Douglass, Nomi L. Harris, Christopher J. Mungall and James A. Overton

    Citation: BMC Bioinformatics 2019 20:407

    Content type: Software

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  28. Missense mutations in the first five exons of F9, which encodes factor FIX, represent 40% of all mutations that cause hemophilia B. To address the ongoing debate regarding in silico identification of disease-caus...

    Authors: Lennon Meléndez-Aranda, Ana Rebeca Jaloma-Cruz, Nina Pastor and Marina María de Jesús Romero-Prado

    Citation: BMC Bioinformatics 2019 20:363

    Content type: Research article

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  30. Parametric feature selection methods for machine learning and association studies based on genetic data are not robust with respect to outliers or influential observations. While rank-based, distribution-free ...

    Authors: Jiaxing Lin, Alexander Sibley, Ivo Shterev, Andrew Nixon, Federico Innocenti, Cliburn Chan and Kouros Owzar

    Citation: BMC Bioinformatics 2019 20:333

    Content type: Software

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  31. The recent success of immunotherapy in treating tumors has attracted increasing interest in research related to the adaptive immune system in the tumor microenvironment. Recent advances in next-generation sequ...

    Authors: Hiroki Konishi, Daisuke Komura, Hiroto Katoh, Shinichiro Atsumi, Hirotomo Koda, Asami Yamamoto, Yasuyuki Seto, Masashi Fukayama, Rui Yamaguchi, Seiya Imoto and Shumpei Ishikawa

    Citation: BMC Bioinformatics 2019 20:267

    Content type: Research article

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  32. Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platfo...

    Authors: Andreas Hofmann, Sarah Preston, Megan Cross, H. M. P. Dilrukshi Herath, Anne Simon and Robin B. Gasser

    Citation: BMC Bioinformatics 2019 20:262

    Content type: Software

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  34. In bacterial genomes, there are two mechanisms to terminate the DNA transcription: the “intrinsic” or Rho-independent termination and the Rho-dependent termination. Intrinsic terminators are characterized by a...

    Authors: Marco Di Salvo, Simone Puccio, Clelia Peano, Stephan Lacour and Pietro Alifano

    Citation: BMC Bioinformatics 2019 20:117

    Content type: Software

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  35. Blood pressure diseases have increasingly been identified as among the main factors threatening human health. How to accurately and conveniently measure blood pressure is the key to the implementation of effec...

    Authors: Bing Zhang, Huihui Ren, Guoyan Huang, Yongqiang Cheng and Changzhen Hu

    Citation: BMC Bioinformatics 2019 20:109

    Content type: Research article

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  36. The investigation of intracellular metabolism is the mainstay in the biotechnology and physiology settings. Intracellular metabolic rates are commonly evaluated using labeling pattern of the identified metabol...

    Authors: Di Du, Lin Tan, Yumeng Wang, Bo Peng, John N. Weinstein, Fredric E. Wondisford, Xiaoyang Su and Philip L. Lorenzi

    Citation: BMC Bioinformatics 2019 20:89

    Content type: Research article

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  37. Drug combinations have the potential to improve efficacy while limiting toxicity. To robustly identify synergistic combinations, high-throughput screens using full dose-response surface are desirable but requi...

    Authors: Arnaud Amzallag, Sridhar Ramaswamy and Cyril H. Benes

    Citation: BMC Bioinformatics 2019 20:83

    Content type: Methodology article

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  40. 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

    Content type: Software

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  41. The consolidation of pathway databases, such as KEGG, Reactome and ConsensusPathDB, has generated widespread biological interest, however the issue of pathway redundancy impedes the use of these consolidated d...

    Authors: Ruth Alexandra Stoney, Jean-Marc Schwartz, David L Robertson and Goran Nenadic

    Citation: BMC Bioinformatics 2018 19:386

    Content type: Research article

    Published on:

  42. Bayesian clustering algorithms, in particular those utilizing Dirichlet Processes (DP), return a sample of the posterior distribution of partitions of a set. However, in many applied cases a single clustering ...

    Authors: Thomas J. Glassen, Timo von Oertzen and Dmitry A. Konovalov

    Citation: BMC Bioinformatics 2018 19:375

    Content type: Research article

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  43. With the exponential growth in available biomedical data, there is a need for data integration methods that can extract information about relationships between the data sets. However, these data sets might hav...

    Authors: Said el Bouhaddani, Hae-Won Uh, Geurt Jongbloed, Caroline Hayward, Lucija Klarić, Szymon M. Kiełbasa and Jeanine Houwing-Duistermaat

    Citation: BMC Bioinformatics 2018 19:371

    Content type: Software

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  44. Data-driven methods that automatically learn relations between attributes from given data are a popular tool for building mathematical models in computational biology. Since measurements are prone to errors, a...

    Authors: Lidija Magdevska, Miha Mraz, Nikolaj Zimic and Miha Moškon

    Citation: BMC Bioinformatics 2018 19:333

    Content type: Methodology article

    Published on:

  45. The inclusion of high-dimensional omics data in prediction models has become a well-studied topic in the last decades. Although most of these methods do not account for possibly different types of variables in...

    Authors: Simon Klau, Vindi Jurinovic, Roman Hornung, Tobias Herold and Anne-Laure Boulesteix

    Citation: BMC Bioinformatics 2018 19:322

    Content type: Methodology article

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  46. Polygenic risk scores (PRS) describe the genomic contribution to complex phenotypes and consistently account for a larger proportion of variance in outcome than single nucleotide polymorphisms (SNPs) alone. Ho...

    Authors: Lawrence M. Chen, Nelson Yao, Elika Garg, Yuecai Zhu, Thao T. T. Nguyen, Irina Pokhvisneva, Shantala A. Hari Dass, Eva Unternaehrer, Hélène Gaudreau, Marie Forest, Lisa M. McEwen, Julia L. MacIsaac, Michael S. Kobor, Celia M. T. Greenwood, Patricia P. Silveira, Michael J. Meaney…

    Citation: BMC Bioinformatics 2018 19:295

    Content type: Software

    Published on:

  49. Circadian rhythms comprise oscillating molecular interactions, the disruption of the homeostasis of which would cause various disorders. To understand this phenomenon systematically, an accurate technique to i...

    Authors: Hitoshi Iuchi, Masahiro Sugimoto and Masaru Tomita

    Citation: BMC Bioinformatics 2018 19:249

    Content type: Research article

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  50. GenoGAM (Genome-wide generalized additive models) is a powerful statistical modeling tool for the analysis of ChIP-Seq data with flexible factorial design experiments. However large runtime and memory requirem...

    Authors: Georg Stricker, Mathilde Galinier and Julien Gagneur

    Citation: BMC Bioinformatics 2018 19:247

    Content type: Software

    Published on:

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