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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Proteomics01:33

Proteomics

9.4K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Updated: Jan 18, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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OmnibusX: A unified platform for accessible multi-omics analysis.

Linh Truong1, Thao Truong1, Huy Nguyen1

  • 1OmnibusXLab, OmnibusX Company Limited, Ho Chi Minh City, Vietnam.

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Summary

OmnibusX offers code-free multi-omics data analysis for researchers, integrating diverse workflows into a single platform. This privacy-centric tool enhances reproducibility and accelerates biological discovery by lowering computational barriers.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Fragmented analytical tools and high computational barriers hinder multi-omics data analysis.
  • Integrating diverse omics data (bulk RNA-seq, single-cell RNA-seq, single-cell ATAC-seq, spatial transcriptomics) presents significant challenges.
  • Lack of user-friendly interfaces and reproducible pipelines limits accessibility for researchers.

Purpose of the Study:

  • To introduce OmnibusX, an integrated, privacy-centric platform for code-free multi-omics data analysis.
  • To consolidate diverse omics data analysis workflows into a single, cohesive application.
  • To lower technical barriers and enhance reproducibility in biological data analysis.

Main Methods:

  • Consolidation of workflows for bulk RNA-seq, single-cell RNA-seq, single-cell ATAC-seq, and spatial transcriptomics.
  • Integration of established open-source tools (Scanpy, DESeq2, SciPy, scikit-learn) into transparent pipelines.
  • Inclusion of proprietary modules: a cell-type prediction engine and an interactive plotting editor.
  • Local data processing via standalone desktop or enterprise editions to ensure privacy.

Main Results:

  • OmnibusX provides a user-friendly, code-free interface for complex multi-omics analysis.
  • The platform ensures data privacy through local processing, eliminating external data transfer.
  • Reproducible pipelines and control over analytical parameters are offered to users.
  • Publication-quality visualizations can be generated using the interactive plotting editor.

Conclusions:

  • OmnibusX effectively bridges computational methodologies with user-friendly interfaces for multi-omics data analysis.
  • The platform accelerates biological discovery by enhancing reproducibility and lowering technical barriers.
  • OmnibusX fosters robust, data-driven collaborations by making advanced analyses more accessible.