Proteomic and interactomic insights into the molecular basis of cell functional diversity

Bludau, Isabell; Aebersold, Ruedi

doi:10.1038/s41580-020-0231-2

Cited by 184 publications

(164 citation statements)

References 135 publications

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“…Minor conversions occurred between other PE categories, with downgrading of PE1 or PE2s and upgrading of PE4s, and even a few PE5s, to PE1s. Although a plethora of studies show low linear correlations (40-60%) between mRNA level and protein abundance 74,75 , our binary data (Fig. 2) supports the contention that once a neXtProt entry has mRNA expression verified, those PE2s are amenable to upgrade to PE1, whereas PE3s, PE4s and particularly PE5s are more resistant to PE1 upgrade.…”

supporting

confidence: 70%

A high-stringency blueprint of the human proteome

et al. 2020

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The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP’s tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.

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confidence: 70%

A high-stringency blueprint of the human proteome

et al. 2020

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“…The method can also applied to other, e.g. multi-omics [38,39] without further modification (proteomic, metabolic and transcriptomic) and carries promise in biological contexts, where suitable (labelled) data and features are available but for which mechanistic models remain elusive. We can also apply ReDX to discern discriminant features in healthy v.s.…”

Section: Discussionmentioning

confidence: 99%

Repeated Decision Stumping Distils Simple Rules from Single Cell Data

Veleslavov

Stumpf

2020

Preprint

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Here we introduce repeated decision stumping, to distill simple models from single cell data. We develop decision trees of depth one – hence ‘stumps’ – to identify in an inductive manner, gene products involved in driving cell fate transitions, and in applications to published data we are able to discover the key-players involved in these processes in an unbiased manner without prior knowledge. The approach is computationally efficient, has remarkable predictive power, and yields robust and statistically stable predictors: the same set of candidates is generated by applying the algorithm to different subsamples of the data.

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“…Signaling mechanisms, such as those proposed above, often involve transient PPIs among regulatory components, which might represent a challenge for their identification due to the limited interaction time or low affinity of each interacting partners (Westermarck et al, 2013). Multiple proteomic approaches have emerged as alternatives to overcome these limitations (Bludau and Aebersold, 2020). These novel approaches could provide new possibilities to identify TRP/Rho GTPases PPIs pathways and give hints of the microdomains where these complexes localize.…”

Section: Outstanding Questions and Future Directionsmentioning

confidence: 99%