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438 result(s) for 'Software' within Volume 20 of BMC Bioinformatics

Page 6 of 9

  1. Next Generation Sequencing (NGS) is a commonly used technology for studying the genetic basis of biological processes and it underpins the aspirations of precision medicine. However, there are significant chal...

    Authors: A. Iacoangeli, A. Al Khleifat, W. Sproviero, A. Shatunov, A. R. Jones, S. L. Morgan, A. Pittman, R. J. Dobson, S. J. Newhouse and A. Al-Chalabi
    Citation: BMC Bioinformatics 2019 20:213
  2. An orthologous group (OG) comprises a set of orthologous and paralogous genes that share a last common ancestor (LCA). OGs are defined with respect to a chosen taxonomic level, which delimits the position of t...

    Authors: Davide Heller, Damian Szklarczyk and Christian von Mering
    Citation: BMC Bioinformatics 2019 20:228
  3. Understanding the phenotypic drug response on cancer cell lines plays a vital role in anti-cancer drug discovery and re-purposing. The Genomics of Drug Sensitivity in Cancer (GDSC) database provides open data ...

    Authors: Pengfei Liu, Hongjian Li, Shuai Li and Kwong-Sak Leung
    Citation: BMC Bioinformatics 2019 20:408
  4. Differences in average signature size were observed with different methods applied. The gene signatures identified by the Latent Effect Adjustment after Primary Projection (LEAPP) method and the methods fitted...

    Authors: Wei Zhou, Karel K. M. Koudijs and Stefan Böhringer
    Citation: BMC Bioinformatics 2019 20:437
  5. Computational approaches for the determination of biologically-active/native three-dimensional structures of proteins with novel sequences have to handle several challenges. The (conformation) space of possibl...

    Authors: Ahmed Bin Zaman and Amarda Shehu
    Citation: BMC Bioinformatics 2019 20:211
  6. Mining epistatic loci which affects specific phenotypic traits is an important research issue in the field of biology. Bayesian network (BN) is a graphical model which can express the relationship between gene...

    Authors: Yang Guo, Zhiman Zhong, Chen Yang, Jiangfeng Hu, Yaling Jiang, Zizhen Liang, Hui Gao and Jianxiao Liu
    Citation: BMC Bioinformatics 2019 20:444
  7. S-sulphenylation is a ubiquitous protein post-translational modification (PTM) where an S-hydroxyl (−SOH) bond is formed via the reversible oxidation on the Sulfhydryl group of cysteine (C). Recent experimenta...

    Authors: Xiaochuan Wang, Chen Li, Fuyi Li, Varun S. Sharma, Jiangning Song and Geoffrey I. Webb
    Citation: BMC Bioinformatics 2019 20:602
  8. Although many of the genic features in Mycobacterium abscessus have been fully validated, a comprehensive understanding of the regulatory elements remains lacking. Moreover, there is little understanding of how t...

    Authors: Patrick M. Staunton, Aleksandra A. Miranda-CasoLuengo, Brendan J. Loftus and Isobel Claire Gormley
    Citation: BMC Bioinformatics 2019 20:466
  9. Several methods to handle data generated from bottom-up proteomics via liquid chromatography-mass spectrometry, particularly for peptide-centric quantification dealing with post-translational modification (PTM...

    Authors: Philip Berg, Evan W. McConnell, Leslie M. Hicks, Sorina C. Popescu and George V. Popescu
    Citation: BMC Bioinformatics 2019 20(Suppl 2):102

    This article is part of a Supplement: Volume 20 Supplement 2

  10. The proposed method was applied to 10 disease pathways. In total, thirty candidate genes were suggested. The result was validated with gene set enrichment analysis software, PubMed literature review and de facto ...

    Authors: Sunjoo Bang, Sangjoon Son, Sooyoung Kim and Hyunjung Shin
    Citation: BMC Bioinformatics 2019 20:74
  11. 2′-O-methylation (2′-O-me or Nm) is a post-transcriptional RNA methylation modified at 2′-hydroxy, which is common in mRNAs and various non-coding RNAs. Previous studies revealed the significance of Nm in mult...

    Authors: Yiran Zhou, Qinghua Cui and Yuan Zhou
    Citation: BMC Bioinformatics 2019 20(Suppl 25):690

    This article is part of a Supplement: Volume 20 Supplement 25

  12. Macrophages show versatile functions in innate immunity, infectious diseases, and progression of cancers and cardiovascular diseases. These versatile functions of macrophages are conducted by different macroph...

    Authors: Ricardo Ramirez, Allen Michael Herrera, Joshua Ramirez, Chunjiang Qian, David W. Melton, Paula K. Shireman and Yu-Fang Jin
    Citation: BMC Bioinformatics 2019 20:725
  13. In systems biology, there is an acute need for integrative approaches in heterogeneous network mining in order to exploit the continuous flux of genomic data. Simultaneous analysis of the metabolic pathways an...

    Authors: Alexandra Zaharia, Bernard Labedan, Christine Froidevaux and Alain Denise
    Citation: BMC Bioinformatics 2019 20:19
  14. When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient’s phenotypes. Typically, this is done through annotation, fil...

    Authors: James M. Holt, Brandon Wilk, Camille L. Birch, Donna M. Brown, Manavalan Gajapathy, Alexander C. Moss, Nadiya Sosonkina, Melissa A. Wilk, Julie A. Anderson, Jeremy M. Harris, Jacob M. Kelly, Fariba Shaterferdosian, Angelina E. Uno-Antonison, Arthur Weborg and Elizabeth A. Worthey
    Citation: BMC Bioinformatics 2019 20:496
  15. Data from genome-wide association studies (GWASs) have been used to estimate the heritability of human complex traits in recent years. Existing methods are based on the linear mixed model, with the assumption ...

    Authors: Xin Li, Dongya Wu, Yue Cui, Bing Liu, Henrik Walter, Gunter Schumann, Chong Li and Tianzi Jiang
    Citation: BMC Bioinformatics 2019 20:219
  16. Pharmacogenomics (PGx) studies how genomic variations impact variations in drug response phenotypes. Knowledge in pharmacogenomics is typically composed of units that have the form of ternary relationships gene v...

    Authors: Pierre Monnin, Joël Legrand, Graziella Husson, Patrice Ringot, Andon Tchechmedjiev, Clément Jonquet, Amedeo Napoli and Adrien Coulet
    Citation: BMC Bioinformatics 2019 20(Suppl 4):139

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

    The Data Descriptor to this article has been published in Scientific Data 2020 7:3

  17. The advent of high-throughput experimental techniques paved the way to genome-wide computational analysis and predictive annotation studies. When considering the joint annotation of a large set of related enti...

    Authors: Stefano Teso, Luca Masera, Michelangelo Diligenti and Andrea Passerini
    Citation: BMC Bioinformatics 2019 20:338
  18. Untargeted metabolomics of host-associated samples has yielded insights into mechanisms by which microbes modulate health. However, data interpretation is challenged by the complexity of origins of the small m...

    Authors: M. Shaffer, K. Thurimella, K. Quinn, K. Doenges, X. Zhang, S. Bokatzian, N. Reisdorph and C. A. Lozupone
    Citation: BMC Bioinformatics 2019 20:614
  19. Super-enhancers (SEs) are clusters of transcriptional active enhancers, which dictate the expression of genes defining cell identity and play an important role in the development and progression of tumors and ...

    Authors: Hongda Bu, Jiaqi Hao, Yanglan Gan, Shuigeng Zhou and Jihong Guan
    Citation: BMC Bioinformatics 2019 20(Suppl 15):598

    This article is part of a Supplement: Volume 20 Supplement 15

  20. Protein feature extraction plays an important role in the areas of similarity analysis of protein sequences and prediction of protein structures, functions and interactions. The feature extraction based on gra...

    Authors: Zengchao Mu, Ting Yu, Enfeng Qi, Juntao Liu and Guojun Li
    Citation: BMC Bioinformatics 2019 20:351
  21. 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
  22. We previously introduced a random-effects model to analyze a set of patients, each of which has two distinct tumors. The goal is to estimate the proportion of patients for which one of the tumors is a metastas...

    Authors: Audrey Mauguen, Venkatraman E. Seshan, Irina Ostrovnaya and Colin B. Begg
    Citation: BMC Bioinformatics 2019 20:555
  23. 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
  24. It has been shown that the deregulation of miRNAs is associated with the development and progression of many human diseases. To reduce time and cost of biological experiments, a number of algorithms have been ...

    Authors: Hailin Chen, Zuping Zhang and Dayi Feng
    Citation: BMC Bioinformatics 2019 20:404
  25. 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
  26. Recent advances in whole-genome sequencing and SNP array technology have led to the generation of a large amount of genotype data. Large volumes of genotype data will require faster and more efficient methods ...

    Authors: Ardalan Naseri, Degui Zhi and Shaojie Zhang
    Citation: BMC Bioinformatics 2019 20(Suppl 11):279

    This article is part of a Supplement: Volume 20 Supplement 11

  27. The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis p...

    Authors: Lech Nieroda, Lukas Maas, Scott Thiebes, Ulrich Lang, Ali Sunyaev, Viktor Achter and Martin Peifer
    Citation: BMC Bioinformatics 2019 20:29
  28. Circular DNA has recently been identified across different species including human normal and cancerous tissue, but short-read mappers are unable to align many of the reads crossing circle junctions hence limi...

    Authors: Iñigo Prada-Luengo, Anders Krogh, Lasse Maretty and Birgitte Regenberg
    Citation: BMC Bioinformatics 2019 20:663
  29. Synthetic lethality has attracted a lot of attentions in cancer therapeutics due to its utility in identifying new anticancer drug targets. Identifying synthetic lethal (SL) interactions is the key step toward...

    Authors: Jiang Huang, Min Wu, Fan Lu, Le Ou-Yang and Zexuan Zhu
    Citation: BMC Bioinformatics 2019 20(Suppl 19):657

    This article is part of a Supplement: Volume 20 Supplement 19

  30. Around 1% of human proteins are predicted to contain a disordered and low complexity prion-like domain (PrLD). Mutations in PrLDs have been shown promote a transition towards an aggregation-prone state in seve...

    Authors: Valentin Iglesias, Oscar Conchillo-Sole, Cristina Batlle and Salvador Ventura
    Citation: BMC Bioinformatics 2019 20:24
  31. Various statistical models have been developed to model the single cell RNA-seq expression profiles, capture its multimodality, and conduct differential gene expression test. However, for expression data gener...

    Authors: Yu Zhang, Changlin Wan, Pengcheng Wang, Wennan Chang, Yan Huo, Jian Chen, Qin Ma, Sha Cao and Chi Zhang
    Citation: BMC Bioinformatics 2019 20(Suppl 24):672

    This article is part of a Supplement: Volume 20 Supplement 24

  32. Cluster analysis is a core task in modern data-centric computation. Algorithmic choice is driven by factors such as data size and heterogeneity, the similarity measures employed, and the type of clusters sough...

    Authors: Yuping Lu, Charles A. Phillips and Michael A. Langston
    Citation: BMC Bioinformatics 2019 20(Suppl 15):503

    This article is part of a Supplement: Volume 20 Supplement 15

  33. One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing F...

    Authors: Adam Thrash, Mark Arick II, Robyn A. Barbato, Robert M. Jones, Thomas A. Douglas, Julie Esdale, Edward J. Perkins and Natàlia Garcia-Reyero
    Citation: BMC Bioinformatics 2019 20(Suppl 2):103

    This article is part of a Supplement: Volume 20 Supplement 2

  34. Next-Generation Sequencing (NGS) is now widely used in biomedical research for various applications. Processing of NGS data requires multiple programs and customization of the processing pipelines according to...

    Authors: Taewoon Joo, Ji-Hye Choi, Ji-Hye Lee, So Eun Park, Youngsic Jeon, Sae Hoon Jung and Hyun Goo Woo
    Citation: BMC Bioinformatics 2019 20:90
  35. High-throughput gene expression technologies provide complex datasets reflecting mechanisms perturbed in an experiment, typically in a treatment versus control design. Analysis of these information-rich data c...

    Authors: Florian Martin, Sylvain Gubian, Marja Talikka, Julia Hoeng and Manuel C. Peitsch
    Citation: BMC Bioinformatics 2019 20:451
  36. Nearly all cellular processes involve proteins structurally rearranging to accommodate molecular partners. The energy landscape underscores the inherent nature of proteins as dynamic molecules interconverting ...

    Authors: David Morris, Tatiana Maximova, Erion Plaku and Amarda Shehu
    Citation: BMC Bioinformatics 2019 20(Suppl 11):280

    This article is part of a Supplement: Volume 20 Supplement 11

  37. Due to the challenging nature of contact prediction, it is beneficial to develop and benchmark a variety of different prediction methods. Our work has produced useful tools with a simple interface that can provid...

    Authors: Joseph Luttrell IV, Tong Liu, Chaoyang Zhang and Zheng Wang
    Citation: BMC Bioinformatics 2019 20(Suppl 2):100

    This article is part of a Supplement: Volume 20 Supplement 2

  38. 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

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