MICOP: Maximal information coefficient-based oscillation prediction to detect biological rhythms in proteomics data

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Abstract

Background

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 identify oscillating molecules among omics datasets must be developed; however, this is still impeded by many difficulties, such as experimental noise and attenuated amplitude.

Results

To address these issues, we developed a new algorithm named Maximal Information Coefficient-based Oscillation Prediction (MICOP), a sine curve-matching method. The performance of MICOP in labeling oscillation or non-oscillation was compared with four reported methods using Mathews correlation coefficient (MCC) values. The numerical experiments were performed with time-series data with (1) mimicking of molecular oscillation decay, (2) high noise and low sampling frequency and (3) one-cycle data. The first experiment revealed that MICOP could accurately identify the rhythmicity of decaying molecular oscillation (MCC > 0.7). The second experiment revealed that MICOP was robust against high-level noise (MCC > 0.8) even upon the use of low-sampling-frequency data. The third experiment revealed that MICOP could accurately identify the rhythmicity of noisy one-cycle data (MCC > 0.8). As an application, we utilized MICOP to analyze time-series proteome data of mouse liver. MICOP identified that novel oscillating candidates numbered 14 and 30 for C57BL/6 and C57BL/6 J, respectively.

Conclusions

In this paper, we presented MICOP, which is an MIC-based algorithm, for predicting periodic patterns in large-scale time-resolved protein expression profiles. The performance test using artificially generated simulation data revealed that the performance of MICOP for decaying data was superior to that of the existing widely used methods. It can reveal novel findings from time-series data and may contribute to biologically significant results. This study suggests that MICOP is an ideal approach for detecting and characterizing oscillations in time-resolved omics data sets.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2257-4) contains supplementary material, which is available to authorized users.

Related collections

Most cited references 29

Record: found
Abstract: found
Article: not found

Comparison of the predicted and observed secondary structure of T4 phage lysozyme.

B W Matthews (1975)

Predictions of the secondary structure of T4 phage lysozyme, made by a number of investigators on the basis of the amino acid sequence, are compared with the structure of the protein determined experimentally by X-ray crystallography. Within the amino terminal half of the molecule the locations of helices predicted by a number of methods agree moderately well with the observed structure, however within the carboxyl half of the molecule the overall agreement is poor. For eleven different helix predictions, the coefficients giving the correlation between prediction and observation range from 0.14 to 0.42. The accuracy of the predictions for both beta-sheet regions and for turns are generally lower than for the helices, and in a number of instances the agreement between prediction and observation is no better than would be expected for a random selection of residues. The structural predictions for T4 phage lysozyme are much less successful than was the case for adenylate kinase (Schulz et al. (1974) Nature 250, 140-142). No one method of prediction is clearly superior to all others, and although empirical predictions based on larger numbers of known protein structure tend to be more accurate than those based on a limited sample, the improvement in accuracy is not dramatic, suggesting that the accuracy of current empirical predictive methods will not be substantially increased simply by the inclusion of more data from additional protein structure determinations.

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Record: found
Abstract: found
Article: not found

Transcriptional architecture and chromatin landscape of the core circadian clock in mammals.

Nobuya Koike, Seung-Hee Yoo, Hung-Chung Huang … (2012)

The mammalian circadian clock involves a transcriptional feed back loop in which CLOCK and BMAL1 activate the Period and Cryptochrome genes, which then feedback and repress their own transcription. We have interrogated the transcriptional architecture of the circadian transcriptional regulatory loop on a genome scale in mouse liver and find a stereotyped, time-dependent pattern of transcription factor binding, RNA polymerase II (RNAPII) recruitment, RNA expression, and chromatin states. We find that the circadian transcriptional cycle of the clock consists of three distinct phases: a poised state, a coordinated de novo transcriptional activation state, and a repressed state. Only 22% of messenger RNA (mRNA) cycling genes are driven by de novo transcription, suggesting that both transcriptional and posttranscriptional mechanisms underlie the mammalian circadian clock. We also find that circadian modulation of RNAPII recruitment and chromatin remodeling occurs on a genome-wide scale far greater than that seen previously by gene expression profiling.

0 comments Cited 608 times – based on 0 reviews      Review now

Record: found
Abstract: found
Article: not found

Molecular architecture of the mammalian circadian clock.

Carrie L. Partch, Carla B Green, Joseph S Takahashi (2014)

Circadian clocks coordinate physiology and behavior with the 24h solar day to provide temporal homeostasis with the external environment. The molecular clocks that drive these intrinsic rhythmic changes are based on interlocked transcription/translation feedback loops that integrate with diverse environmental and metabolic stimuli to generate internal 24h timing. In this review we highlight recent advances in our understanding of the core molecular clock and how it utilizes diverse transcriptional and post-transcriptional mechanisms to impart temporal control onto mammalian physiology. Understanding the way in which biological rhythms are generated throughout the body may provide avenues for temporally directed therapeutics to improve health and prevent disease. Copyright © 2013 Elsevier Ltd. All rights reserved.

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Author and article information

Contributors

Hitoshi Iuchi: hiuchi@sfc.keio.ac.jp

Masahiro Sugimoto: msugi@sfc.keio.ac.jp

Masaru Tomita: mt@sfc.keio.ac.jp

Journal

Journal ID (nlm-ta): BMC Bioinformatics

Journal ID (iso-abbrev): BMC Bioinformatics

Title: BMC Bioinformatics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2105

Publication date (Electronic): 28 June 2018

Publication date PMC-release: 28 June 2018

Publication date Collection: 2018

Volume: 19

Electronic Location Identifier: 249

Affiliations

[1 ]ISNI 0000 0004 1936 9959, GRID grid.26091.3c, Systems Biology Program, Graduate School of Media and Governance, , Keio University, ; Fujisawa, 252-8520 Japan

[2 ]ISNI 0000 0004 1936 9959, GRID grid.26091.3c, Institute for Advanced Biosciences, , Keio University, ; Tsuruoka, 997-0052 Japan

[3 ]ISNI 0000 0001 0663 3325, GRID grid.410793.8, Health Promotion and Preemptive Medicine, Research and Development Center for Minimally Invasive Therapies, , Tokyo Medical University, ; Shinjuku, Tokyo, 160-0022 Japan

[4 ]ISNI 0000 0004 1936 9959, GRID grid.26091.3c, Department of Environment and Information Studies, , Keio University, ; Fujisawa, 252-8520 Japan

Article

Publisher ID: 2257

DOI: 10.1186/s12859-018-2257-4

PMC ID: 6025708

PubMed ID: 29954316

SO-VID: 8e464c97-6099-4c34-acb6-101c7cae7660

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.