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Related Concept Videos

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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Updated: Sep 30, 2025

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MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks.

Aleksandar Anžel1, Dominik Heider1, Georges Hattab1

  • 1Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Strasse 6, Marburg 35032, Hesse, Germany.

Computational and Structural Biotechnology Journal
|March 14, 2022
PubMed
Summary
This summary is machine-generated.

Researchers can now explore complex time-series multi-omics data with MOVIS, a new web tool. This platform integrates different data types for better pattern discovery and anomaly detection in biological research.

Keywords:
Data explorationLongitudinal multi-omicsMulti-omicsTemporal multi-omicsTime-seriesVisualization

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Science

Background:

  • Advances in sequencing and computational technologies generate multi-temporal, multi-modal biological datasets.
  • Exploring these complex datasets is challenging due to the separation of individual omics data types.
  • Expertise in computer science and bioinformatics is often required for effective temporal data analysis.

Purpose of the Study:

  • To present MOVIS, a user-friendly web interface for exploring time-series multi-omics data.
  • To enable integrated analysis and visualization of diverse omics data types.
  • To facilitate pattern discovery, anomaly detection, and understanding of temporal biological processes.

Main Methods:

  • Development of MOVIS, a modular, open-source software tool.
  • Implementation of a user-friendly web interface for data exploration.
  • Integration and reproduction of two time-series multi-omics datasets.

Main Results:

  • MOVIS effectively integrates and analyzes time-series multi-omics data.
  • The tool provides task-specific, reproducible, and publication-ready visualizations.
  • Successful reproduction of two benchmark time-series multi-omics datasets validates the platform.

Conclusions:

  • MOVIS democratizes the exploration of time-series multi-omics data.
  • The platform enhances biological and medical research by facilitating integrated data analysis.
  • MOVIS is extensible and accessible online and via Docker Hub.