Themed collection Emerging Investigators
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Contributors to our Emerging Investigators issue
This profile offers an insight into some of the -omics researchers who have contributed to this Emerging Investigators themed collection. Congratulations to all of the authors featured!
Mol. Omics, 2022,18, 696-698
https://doi.org/10.1039/D2MO90022J
Mass spectrometry-based proteomics in neurodegenerative lysosomal storage disorders
The lysosome is indispensable and plays many critical roles in the cell, therefore, diseases associated with lysosomal failure can be lethal, particularly lysosomal storage disorders. Figure is created with BioRender.com.
Mol. Omics, 2022,18, 256-278
https://doi.org/10.1039/D2MO00004K
Computational approaches leveraging integrated connections of multi-omic data toward clinical applications
Data integration approaches are crucial for transforming multi-omic data sets into clinically interpretable knowledge. This review presents a detailed and extensive guideline to catalog the recent computational multi-omic data integration methods.
Mol. Omics, 2022,18, 7-18
https://doi.org/10.1039/D1MO00158B
Interrogating the transcriptome with metabolically incorporated ribonucleosides
This review summarizes recent developments in metabolic labeling of RNA to study RNA synthesis and turnover, RNA binding proteins, and RNA modifications and modifying enzymes.
Mol. Omics, 2021,17, 833-841
https://doi.org/10.1039/D1MO00334H
Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum
High grade serous ovarian cancer is the most common and deadly subtype of ovarian cancer and has a distinct pattern of metastasis originating in the fallopian tube and then it metastasizes first to the ovary, and later to the omentum.
Mol. Omics, 2021,17, 819-832
https://doi.org/10.1039/D1MO00074H
Enhanced detection and annotation of small molecules in metabolomics using molecular-network-oriented parameter optimization
An integrated molecular-network-based optimization strategy for enhanced metabolomics analysis is reported.
Mol. Omics, 2021,17, 665-676
https://doi.org/10.1039/D1MO00005E
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Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer
Multi-omics data integration of triple negative breast cancer (TNBC) provides insight into biological pathways.
Mol. Omics, 2021,17, 677-691
https://doi.org/10.1039/D1MO00117E
Data-independent acquisition-based proteome and phosphoproteome profiling across six melanoma cell lines reveals determinants of proteotypes
We present a high-quality data-independent acquisition dataset, profiling the abundance and variation of both proteomes and phosphoproteomes across melanoma cells.
Mol. Omics, 2021,17, 413-425
https://doi.org/10.1039/D0MO00188K
Guide for protein fold change and p-value calculation for non-experts in proteomics
Proteomics data can be processed using simple speadsheet formula.
Mol. Omics, 2020,16, 573-582
https://doi.org/10.1039/D0MO00087F
About this collection
This collection highlights the excellent work being carried out by the rising stars and tomorrow’s leaders in the field of the -omics research community.
New articles will be added to the collection upon publication; please return to this page frequently to see the collection grow.