Author

Nhung Pham

Maastricht UniversityORCID 0000-0003-3091-3962Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Nhung Pham1 paper · The University of Texas MD Anderson Cancer Center

Biology Disciplines

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Systems Biology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:database / resource· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1

Frequent Co-Authors

Akira FunahashiiD· 2 shared Alexander MazeiniD· 2 shared Angela BauchiD· 2 shared Anna NiarakisiD· 2 shared Arnau MontagudiD· 2 shared Augustin LunaiD· 2 shared Benjamin M. GyoriiD· 2 shared Bijay JassaliD· 2 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersSystems Biology

Akira FunahashiORCID

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3 papers

Recent·Most cited

Systems BiologybioRxivPreprintDec 17, 2022

A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

Anna Niarakis, Marek Ostaszewski, Alexander Mazein…·the COVID-19 Disease Map Community

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.

1 citation

humanbulk RNA-seq

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Systems BiologyMolecular Systems BiologyPeer-reviewedOct 1, 2021

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

Marek Ostaszewski, Anna Niarakis, Alexander Mazein…·Özgün Babur

The paper describes the development of a computational knowledge repository, the COVID-19 Disease Map, which curates SARS-CoV-2 virus-host interaction mechanisms and provides tools for their analysis and application.

101 citationstop 1%

statistical modeldatabase / resource

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BioinformaticsMetabolitesPeer-reviewedFeb 6, 2019

Consistency, Inconsistency and Ambiguity of Metabolite Names in Biochemical Databases Used for Genome Scale Metabolic Modelling

Nhung Pham, Ruben G. A. van Heck, Jesse C. J. van Dam…·Maria Suarez Diez

This study examines name inconsistencies and ambiguities in biochemical databases used for genome-scale metabolic modeling, finding up to 83.1% inconsistency and proposing solutions for better mapping.

44 citations

metabolomicsstatistical model

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