PhD Scientific Days 2025

Poster Session I. - A: Molecular Medicine

Update of Compartmentalization Databases (ComPPI, Translocatome) for Logical Modelling

Előadó neve

Mr. Kerestély Márk

Neptun code

FP0TED

Előadó munkahelye

Semmelweis University, Department of Molecular Biology

Előadó telefonszáma

+36305362937

Előadó e-mail címe

akermar18@gmail.com

Az előadás címe

Update of Compartmentalization Databases (ComPPI, Translocatome) for Logical Modelling

Szerző(k) neve és munkahelye

Márk Kerestély¹, István Narozsny¹, Réka Czinege¹, Dániel Veres², Péter Csermely¹

1: Semmelweis University, Department of Molecular Biology
2: Turbine Ltd.

Bemutatás módja

Poszter

Szekció

Poster Session I. - A: Molecular Medicine

Language of the presentation

English

Preferred session

Molecular Medicine

Összefoglaló szövege

Introduction: For a deeper understanding of eukaryotic cell function, it is essential to map the localization of proteins and their translocations between subcellular compartments. Previously, our research group created the ComPPI database, which integrates compartmentalized protein-protein interactions, and the Translocatome database, which contains data and predictions on protein translocations. Compartmentalization data is highly useful for logical network models (like Boolean models) that can cost-effectively model complex biological systems.
Aims: Our goal was to update ComPPI and Translocatome and make them suitable for utilization in logical modelling. We also aimed to validate the previous predictions of Translocatome.
Method: We utilized the “The Minimum Information about a Molecular Interaction CAusal Statement” (MI2CAST) guidelines and the MITAB data format in the update of ComPPI and Translocatome. For the validation of Translocatome’s predictions, we manually curated translocating and non-translocating proteins and described the performance of these predictions with measures of diagnostic accuracy (e.g. ROC AUC, F1-score, MCC).
Results: We updated ComPPI and Translocatome based on the MI2CAST guidelines and integrated data into them about post-translational modifications, biological functions and protein complexes. We collected and validated 402 translocating proteins from the Reactome, UniProt and Signor databases and 162 non-translocating proteins from the UniProt, ComPPI and HPA databases. Based on these curated proteins, the statistical analysis of previous predictions of Translocatome resulted in ROC AUC = 0,73, F1 = 0,68, MCC = 0,37.
Conclusion: The update of ComPPI and Translocatome facilitates their use in logical modelling of complex biological systems. The Translocatome prediction model performed reasonably well. The curated data can be used to further train the model.
Funding: Supported by the Thematic Excellence Program (Tématerületi Kiválósági Program TKP2021-EGA-24) of the Ministry for Innovation and Technology in Hungary, within the framework of the Molecular Biology thematic program of the Semmelweis University and by the 2024–2.1.1-EKÖP-2024–00004 University Research Scholarship Programme of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund.

University

Semmelweis University

Supervisor

Prof. Péter Csermely

Publication of my abstract

I give consent to the publication of my abstract on the website of the congress.

phd.section.field

before finishing undergraduate studies (TDK, MD-PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

8257

Start

17:48

End

17:54