State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing

Krassowski, Michal; Das, Vivek; Sahu, Shivani; Misra, Biswapriya B.

doi:10.3389/fgene.2020.610798

Cited by 240 publications

(155 citation statements)

References 87 publications

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“…Multiple repositories were launched to enhance metabolomics data sharing, and, in parallel, tools that integrate the data from different repositories were recently developed ( Krassowski et al, 2020 ; Palermo et al, 2020 ). Examples for such repositories include MetaboLights, GNPS-MASSIVE, and Metabolomics Workbench ( Haug et al, 2013 ; Sud et al, 2016 ; Wang et al, 2016 ).…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

The History of Gene Hunting in Hereditary Spinocerebellar Degeneration: Lessons From the Past and Future Perspectives

Stevanin

2021

Front. Genet.

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Hereditary spinocerebellar degeneration (SCD) encompasses an expanding list of rare diseases with a broad clinical and genetic heterogeneity, complicating their diagnosis and management in daily clinical practice. Correct diagnosis is a pillar for precision medicine, a branch of medicine that promises to flourish with the progressive improvements in studying the human genome. Discovering the genes causing novel Mendelian phenotypes contributes to precision medicine by diagnosing subsets of patients with previously undiagnosed conditions, guiding the management of these patients and their families, and enabling the discovery of more causes of Mendelian diseases. This new knowledge provides insight into the biological processes involved in health and disease, including the more common complex disorders. This review discusses the evolution of the clinical and genetic approaches used to diagnose hereditary SCD and the potential of new tools for future discoveries.

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Section: Discussion and Future Directionsmentioning

confidence: 99%

The History of Gene Hunting in Hereditary Spinocerebellar Degeneration: Lessons From the Past and Future Perspectives

Stevanin

2021

Front. Genet.

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“…Because of the interconnected nature of cell signaling, targeting transcription factors, which act downstream in the signaling process, is a more specific strategy than focusing on the expression on upstream cell-signaling nodes. The strategy that we have developed allows to overcome some of the limitations of standard drug repurposing approaches based on the screening of a large number of compounds by cell assays [43], [44]. Our strategy, however, has some limitations as the CMap resource has incomplete drug coverage.…”

Section: Discussionmentioning

confidence: 99%

Transcription Factor Activation Profiles (TFAP) identify compounds promoting differentiation of Acute Myeloid Leukemia cell lines

Riccio

Micarelli

Secci

et al. 2021

Preprint

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Repurposing of drugs for new therapeutic use has received considerable attention for its potential to reduce time and cost of drug development. Here we present a new strategy to identify chemicals that are likely to induce differentiation of leukemic cells. As Acute Myeloid Leukemia (AML) is the result of a block in myeloid differentiation, finding new drugs that are capable of inducing blast terminal maturation is considered a valuable strategy. We used data from the Connectivity Map (CMap) to identify drugs that could be repositioned for their potential to activate transcription factors that mediate myeloid differentiation. Compounds promoting the activation of transcription factors that play a positive role in myeloid differentiation were considered candidate pro-differentiation drugs. This approach yielded a list of chemicals ranked according to the potential to activate transcription factors that induce differentiation of leukemic progenitor cells. Drugs that are already used in differentiation therapy, such as for instance all-trans retinoic acid (ATRA) are in the top positions of this ranked list. To validate our strategy, we tested the in vitro differentiation potential of 22 candidate compounds using the HL-60 human cell line as a myeloid differentiation model. Ten out of 22 compounds, ranking high in the inferred list, were confirmed to induce significant differentiation of HL-60. Some of these compounds are known to trigger the DNA damage response, thus identifying this process as a target to modulate myeloid differentiation. These results underscore the potential of our approach to accelerate the drug discovery process. The method that we have developed is highly versatile and it can be adapted to different drug repurposing projects.

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“…Metabolomics datasets play an indispensable role in multi-omics data integration and analytics workflows as metabolites are the closest to the phenotype and helps connect with the genotype (Fiehn, 2002 ). Recent efforts in multi-omics domain encompass harmonization of quality metrics and power calculation in multi-omic studies (Tarazona et al 2020 ) to standardized data sharing guidelines (Krassowski et al 2020 ). A recent review introduced the tools for computational methods and resources in metabolomics and multiomics integration (Eicher et al 2020 ).…”

Section: Other Specialized Toolsmentioning

confidence: 99%

New software tools, databases, and resources in metabolomics: updates from 2020

Misra

2021

Metabolomics

Self Cite

149

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Background Precision medicine, space exploration, drug discovery to characterization of dark chemical space of habitats and organisms, metabolomics takes a centre stage in providing answers to diverse biological, biomedical, and environmental questions. With technological advances in mass-spectrometry and spectroscopy platforms that aid in generation of information rich datasets that are complex big-data, data analytics tend to co-evolve to match the pace of analytical instrumentation. Software tools, resources, databases, and solutions help in harnessing the concealed information in the generated data for eventual translational success. Aim of the review In this review, ~ 85 metabolomics software resources, packages, tools, databases, and other utilities that appeared in 2020 are introduced to the research community. Key scientific concepts of review In Table 1 the computational dependencies and downloadable links of the tools are provided, and the resources are categorized based on their utility. The review aims to keep the community of metabolomics researchers updated with all the resources developed in 2020 at a collated avenue, in line with efforts form 2015 onwards to help them find these at one place for further referencing and use.

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State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing

Cited by 240 publications

References 87 publications

The History of Gene Hunting in Hereditary Spinocerebellar Degeneration: Lessons From the Past and Future Perspectives

The History of Gene Hunting in Hereditary Spinocerebellar Degeneration: Lessons From the Past and Future Perspectives

Transcription Factor Activation Profiles (TFAP) identify compounds promoting differentiation of Acute Myeloid Leukemia cell lines

New software tools, databases, and resources in metabolomics: updates from 2020

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