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  1. The sequencing platform BGISEQ-500 is based on DNBSEQ technology and provides high throughput with low costs. This sequencer has been widely used in various areas of scientific and clinical research. A better ...

    Authors: Yanqiu Zhou, Chen Liu, Rongfang Zhou, Anzhi Lu, Biao Huang, Liling Liu, Ling Chen, Bei Luo, Jin Huang and Zhijian Tian
    Citation: BioData Mining 2019 12:21
  2. Gerontogenes include those that modulate life expectancy in various species and may be the actual longevity genes. We believe that a long (relative to body weight) lifespan in individual rodent and primate spe...

    Authors: Lev I. Rubanov, Andrey G. Zaraisky, Gregory A. Shilovsky, Alexandr V. Seliverstov, Oleg A. Zverkov and Vassily A. Lyubetsky
    Citation: BioData Mining 2019 12:20
  3. Incidence and mortality of lung cancer have dramatically decreased during the last decades, yet still approximately 160,000 deaths per year occurred in United States. Smoking intensity, duration, starting age,...

    Authors: Bidong Ma, Zhiyou Huang, Qian Wang, Jizhou Zhang, Bin Zhou and Jiaohong Wu
    Citation: BioData Mining 2019 12:18
  4. The clinical outcomes of patients with resected T1-3N0–2M0 non-small cell lung cancer (NSCLC) with the same tumor-node-metastasis (TNM) stage are diverse. Although other prognostic factors and prognostic predicti...

    Authors: Yunkui Zhang, YaoChen Li, Rongsheng Zhang, Yujie Zhang and Haitao Ma
    Citation: BioData Mining 2019 12:17
  5. The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontolog...

    Authors: Aurélien Brionne, Amélie Juanchich and Christelle Hennequet-Antier
    Citation: BioData Mining 2019 12:16
  6. Widespread adoption of Electronic Health Records (EHR) increased the number of reported disease association studies, or Phenome-Wide Association Studies (PheWAS). Traditional PheWAS studies ignore visit type (i.e...

    Authors: Mary Regina Boland, Snigdha Alur-Gupta, Lisa Levine, Peter Gabriel and Graciela Gonzalez-Hernandez
    Citation: BioData Mining 2019 12:15
  7. The principal line of investigation in Genome Wide Association Studies (GWAS) is the identification of main effects, that is individual Single Nucleotide Polymorphisms (SNPs) which are associated with the trai...

    Authors: Elisabetta Manduchi, Patryk R. Orzechowski, Marylyn D. Ritchie and Jason H. Moore
    Citation: BioData Mining 2019 12:14
  8. Fraudulent milk adulteration is a dangerous practice in the dairy industry that is harmful to consumers since milk is one of the most consumed food products. Milk quality can be assessed by Fourier Transformed...

    Authors: Habib Asseiss Neto, Wanessa L.F. Tavares, Daniela C.S.Z. Ribeiro, Ronnie C.O. Alves, Leorges M. Fonseca and Sérgio V.A. Campos
    Citation: BioData Mining 2019 12:13
  9. Tremendous amount of whole-genome sequencing data have been provided by large consortium projects such as TCGA (The Cancer Genome Atlas), COSMIC and so on, which creates incredible opportunities for functional...

    Authors: Jia-Hao Bi, Yi-Fan Tong, Zhe-Wei Qiu, Xing-Feng Yang, John Minna, Adi F. Gazdar and Kai Song
    Citation: BioData Mining 2019 12:12
  10. In Genome-Wide Association Studies (GWAS), the concept of linkage disequilibrium is important as it allows identifying genetic markers that tag the actual causal variants. In Genome-Wide Association Interactio...

    Authors: Marc Joiret, Jestinah M. Mahachie John, Elena S. Gusareva and Kristel Van Steen
    Citation: BioData Mining 2019 12:11

    The Correction to this article has been published in BioData Mining 2022 15:11

  11. DNA methylation is an epigenetic event that may regulate gene expression. Because of this regulation role, aberrant DNA methylation is often associated with many diseases. Within-sample DNA co-methylation is t...

    Authors: Lillian Sun and Shuying Sun
    Citation: BioData Mining 2019 12:9
  12. Most existing algorithms for modeling and analyzing molecular networks assume a static or time-invariant network topology. Such view, however, does not render the temporal evolution of the underlying biologica...

    Authors: Gregory Ditzler, Nidhal Bouaynaya, Roman Shterenberg and Hassan M. Fathallah-Shaykh
    Citation: BioData Mining 2019 12:5
  13. Machine learning strategies are prominent tools for data analysis. Especially in life sciences, they have become increasingly important to handle the growing datasets collected by the scientific community. Mea...

    Authors: Sebastian Bittrich, Marika Kaden, Christoph Leberecht, Florian Kaiser, Thomas Villmann and Dirk Labudde
    Citation: BioData Mining 2019 12:1
  14. One strategy for addressing missing heritability in genome-wide association study is gene-gene interaction analysis, which, unlike a single gene approach, involves high-dimensionality. The multifactor dimensio...

    Authors: Seungyeoun Lee, Donghee Son, Yongkang Kim, Wenbao Yu and Taesung Park
    Citation: BioData Mining 2018 11:27
  15. Metagenomic surveys of human microbiota are becoming increasingly widespread in academic research as well as in food and pharmaceutical industries and clinical context. Intuitive tools for investigating experi...

    Authors: Daria Efimova, Alexander Tyakht, Anna Popenko, Anatoly Vasilyev, Ilya Altukhov, Nikita Dovidchenko, Vera Odintsova, Natalya Klimenko, Robert Loshkarev, Maria Pashkova, Anna Elizarova, Viktoriya Voroshilova, Sergei Slavskii, Yury Pekov, Ekaterina Filippova, Tatiana Shashkova…
    Citation: BioData Mining 2018 11:25
  16. It is becoming increasingly clear that the quantification of mitochondria and synapses is of great significance to understand the function of biological nervous systems. Electron microscopy (EM), with the nece...

    Authors: Weifu Li, Jing Liu, Chi Xiao, Hao Deng, Qiwei Xie and Hua Han
    Citation: BioData Mining 2018 11:24
  17. ReliefF is a nearest-neighbor based feature selection algorithm that efficiently detects variants that are important due to statistical interactions or epistasis. For categorical predictors, like genotypes, th...

    Authors: M. Arabnejad, B. A. Dawkins, W. S. Bush, B. C. White, A. R. Harkness and B. A. McKinney
    Citation: BioData Mining 2018 11:23
  18. Searching for interesting common subgraphs in graph data is a well-studied problem in data mining. Subgraph mining techniques focus on the discovery of patterns in graphs that exhibit a specific network struct...

    Authors: Aida Mrzic, Pieter Meysman, Wout Bittremieux, Pieter Moris, Boris Cule, Bart Goethals and Kris Laukens
    Citation: BioData Mining 2018 11:20
  19. The redundancy of information is becoming a critical issue for epidemiologists. High-dimensional datasets require new effective variable selection methods to be developed. This study implements an advanced evo...

    Authors: Christina Brester, Jussi Kauhanen, Tomi-Pekka Tuomainen, Sari Voutilainen, Mauno Rönkkö, Kimmo Ronkainen, Eugene Semenkin and Mikko Kolehmainen
    Citation: BioData Mining 2018 11:18
  20. The function of a protein is determined by its native protein structure. Among many protein prediction methods, the Hydrophobic-Polar (HP) model, an ab initio method, simplifies the protein folding prediction ...

    Authors: Cheng-Hong Yang, Kuo-Chuan Wu, Yu-Shiun Lin, Li-Yeh Chuang and Hsueh-Wei Chang
    Citation: BioData Mining 2018 11:17
  21. Biologists aim to understand the genetic background of diseases, metabolic disorders or any other genetic condition. Microarrays are one of the main high-throughput technologies for collecting information abou...

    Authors: Jorge Parraga-Alava, Marcio Dorn and Mario Inostroza-Ponta
    Citation: BioData Mining 2018 11:16
  22. Triclustering has shown to be a valuable tool for the analysis of microarray data since its appearance as an improvement of classical clustering and biclustering techniques. The standard for validation of tric...

    Authors: David Gutiérrez-Avilés, Raúl Giráldez, Francisco Javier Gil-Cumbreras and Cristina Rubio-Escudero
    Citation: BioData Mining 2018 11:15
  23. Investigators often interpret genome-wide data by analyzing the expression levels of genes within pathways. While this within-pathway analysis is routine, the products of any one pathway can affect the activit...

    Authors: Kathleen M. Chen, Jie Tan, Gregory P. Way, Georgia Doing, Deborah A. Hogan and Casey S. Greene
    Citation: BioData Mining 2018 11:14
  24. Human microbiome studies in clinical settings generally focus on distinguishing the microbiota in health from that in disease at a specific point in time. However, microbiome samples may be associated with dis...

    Authors: Laura Tipton, Karen T. Cuenco, Laurence Huang, Ruth M. Greenblatt, Eric Kleerup, Frank Sciurba, Steven R. Duncan, Michael P. Donahoe, Alison Morris and Elodie Ghedin
    Citation: BioData Mining 2018 11:12
  25. In text mining, document clustering describes the efforts to assign unstructured documents to clusters, which in turn usually refer to topics. Clustering is widely used in science for data retrieval and organi...

    Authors: Jens Dörpinghaus, Sebastian Schaaf and Marc Jacobs
    Citation: BioData Mining 2018 11:11
  26. The Toxicological Priority Index (ToxPi) is a method for prioritization and profiling of chemicals that integrates data from diverse sources. However, individual data sources (“assays”), such as in vitro bioas...

    Authors: Kimberly T. To, Rebecca C. Fry and David M. Reif
    Citation: BioData Mining 2018 11:10
  27. Gene set analysis is a valuable tool to summarize high-dimensional gene expression data in terms of biologically relevant sets. This is an active area of research and numerous gene set analysis methods have be...

    Authors: Ravi Mathur, Daniel Rotroff, Jun Ma, Ali Shojaie and Alison Motsinger-Reif
    Citation: BioData Mining 2018 11:8
  28. Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remai...

    Authors: Shefali S. Verma, Anastasia Lucas, Xinyuan Zhang, Yogasudha Veturi, Scott Dudek, Binglan Li, Ruowang Li, Ryan Urbanowicz, Jason H. Moore, Dokyoon Kim and Marylyn D. Ritchie
    Citation: BioData Mining 2018 11:5
  29. Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be use...

    Authors: Juan A. Nepomuceno, Alicia Troncoso, Isabel A. Nepomuceno-Chamorro and Jesús S. Aguilar-Ruiz
    Citation: BioData Mining 2018 11:4
  30. Evolutionary computation (EC) has been widely applied to biological and biomedical data. The practice of EC involves the tuning of many parameters, such as population size, generation count, selection size, an...

    Authors: Moshe Sipper, Weixuan Fu, Karuna Ahuja and Jason H. Moore
    Citation: BioData Mining 2018 11:2

    The Correction to this article has been published in BioData Mining 2019 12:22

  31. Survival analysis is a statistical technique widely used in many fields of science, in particular in the medical area, and which studies the time until an event of interest occurs. Outlier detection in this co...

    Authors: Eunice Carrasquinha, André Veríssimo, Marta B. Lopes and Susana Vinga
    Citation: BioData Mining 2018 11:1

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