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Big Data in Multi-Omics
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Big Data in Multi-Omics

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 20 August 2025 | Viewed by 2898

Special Issue Editors

Prof. Dr. Dimitrios Vlachakis

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Guest Editor
Genetics Laboratory, Agricultural University of Athens, Athens, Greece
Interests: genetics; epigenetics; exosomes; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. George P. Chrousos

E-Mail Website
Guest Editor
University Research Institute of Maternal and Child Health and Precision Medicine, Medical School, “Aghia Sophia” Children’s Hospital, National and Kapodistrian University of Athens, 15772 Athens, Greece
Interests: genetics; epigenetics; exosomes; endocrinology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will focus on how to analyze, manage, communicate, process, model, and exploit big data using conventional or high-performance computing in the field of multi-omics. The main axes will be genomics, transcriptomics, proteomics, metabolomics, and epigenomics. Multi-omics integrates these diverse types of biological data to provide a comprehensive understanding of biological systems and processes. However, multi-omics generates massive amounts of data from different sources and technologies (e.g., next-generation sequencing (NGS) and mass spectrometry) that, most of the time, are hetegeneous and non-standardized. This Special Issue will focus on state-of-the-art techniques that can be used to analyze -omics datasets, whilst ensuring data quality and accuracy are maintained, given the diverse and complex nature of multi-omics information. Focus will be on advanced analytical techniques, including machine learning, artificial intelligence, and network analysis, and how they are used to extract meaningful insights from the integrated multi-omics data. Moreover, this Special Issue will address the need for combining data from multiple omics layers with sophisticated computational tools and algorithms that are necessary to integrate and interpret the data, uncovering complex biological relationships and networks. The goal is to efficiently exploit all -omics information in an effort to gain holistic views of biological systems and drive forward scientific and medical advancements.

Prof. Dr. Dimitrios Vlachakis
Prof. Dr. George P. Chrousos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • data science
  • big data
  • omics
  • data management
  • data analytics
 

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Published Papers (2 papers)

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Research

32 pages, 10662 KiB  
Article
Characterization of Exhausted T Cell Signatures in Pan-Cancer Settings
by Rifat Tasnim Juthi, Saiful Arefeen Sazed, Manvita Mareboina, Apostolos Zaravinos and Ilias Georgakopoulos-Soares
Int. J. Mol. Sci. 2025, 26(5), 2311; https://doi.org/10.3390/ijms26052311 - 5 Mar 2025
Viewed by 881
Abstract
T cells play diverse roles in cancer immunology, acting as tumor suppressors, cytotoxic effectors, enhancers of cytotoxic T lymphocyte responses and immune suppressors; providing memory and surveillance; modulating the tumor microenvironment (TME); or activating innate immune cells. However, cancer cells can disrupt T [...] Read more.
T cells play diverse roles in cancer immunology, acting as tumor suppressors, cytotoxic effectors, enhancers of cytotoxic T lymphocyte responses and immune suppressors; providing memory and surveillance; modulating the tumor microenvironment (TME); or activating innate immune cells. However, cancer cells can disrupt T cell function, leading to T cell exhaustion and a weakened immune response against the tumor. The expression of exhausted T cell (Tex) markers plays a pivotal role in shaping the immune landscape of multiple cancers. Our aim was to systematically investigate the role of known T cell exhaustion (Tex) markers across multiple cancers while exploring their molecular interactions, mutation profiles, and potential implications for immunotherapy. The mRNA expression profile of six Tex markers, LAG-3, PDCD1, TIGIT, HAVCR2, CXCL13, and LAYN was investigated in pan-cancer. Utilizing data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), The Cancer Proteome Atlas (TCPA), and other repositories, we characterized the differential expression of the Tex markers, their association with the patients’ survival outcome, and their mutation profile in multiple cancers. Additionally, we analyzed the effects on cancer-related pathways and immune infiltration within the TME, offering valuable insights into mechanisms of cancer immune evasion and progression. Finally, the correlation between their expression and sensitivity to multiple anti-cancer drugs was investigated extensively. Differential expression of all six markers was significantly associated with KIRC and poor prognosis in several cancers. They also played a potential activating role in apoptosis, EMT, and hormone ER pathways, as well as a potential inhibitory role in the DNA damage response and RTK oncogenic pathways. Infiltration of different immune cells was also found to be associated with the expression of the Tex-related genes in most cancer types. These findings underline that the reviving of exhausted T cells can be used to enhance the efficacy of immunotherapy in cancer patients. Full article
(This article belongs to the Special Issue Big Data in Multi-Omics)
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18 pages, 10223 KiB  
Article
Integrating Single-Cell RNA-Seq and ATAC-Seq Analysis Reveals Uterine Cell Heterogeneity and Regulatory Networks Linked to Pimpled Eggs in Chickens
by Wenqiang Li, Xueying Ma, Xiaomin Li, Xuguang Zhang, Yifei Sun, Chao Ning, Qin Zhang, Dan Wang and Hui Tang
Int. J. Mol. Sci. 2024, 25(24), 13431; https://doi.org/10.3390/ijms252413431 - 15 Dec 2024
Viewed by 1515
Abstract
Pimpled eggs have defective shells, which severely impacts hatching rates and transportation safety. In this study, we constructed single-cell resolution transcriptomic and chromatin accessibility maps from uterine tissues of chickens using single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq). We identified 11 [...] Read more.
Pimpled eggs have defective shells, which severely impacts hatching rates and transportation safety. In this study, we constructed single-cell resolution transcriptomic and chromatin accessibility maps from uterine tissues of chickens using single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq). We identified 11 major cell types and characterized their marker genes, along with specific transcription factors (TFs) that determine cell fate. CellChat analysis showed that fibroblasts had the most extensive intercellular communication network and that the chickens laying pimpled eggs had amplified immune-related signaling pathways. Differential expression and enrichment analyses indicated that inflammation in pimpled egg-laying chickens may lead to disruptions in their circadian rhythm and changes in the expression of ion transport-related genes, which negatively impacts eggshell quality. We then integrated TF analysis to construct a regulatory network involving TF–target gene–Gene Ontology associations related to pimpled eggs. We found that the transcription factors ATF3, ATF4, JUN, and FOS regulate uterine activities upstream, while the downregulation of ion pumps and genes associated with metal ion binding directly promotes the formation of pimpled eggs. Finally, by integrating the results of scRNA-seq and scATAC-seq, we identified a rare cell type—ionocytes. Our study constructed single-cell resolution transcriptomic and chromatin accessibility maps of chicken uterine tissue and explored the molecular regulatory mechanisms underlying pimpled egg formation. Our findings provide deeper insights into the structure and function of the chicken uterus, as well as the molecular mechanisms of eggshell formation. Full article
(This article belongs to the Special Issue Big Data in Multi-Omics)
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