In-silico prediction and mass spectrometric validation of the Aspergillus niger secretome

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DOI: 10.34701/ibisba.1.investigation.8.1

Zenodo URL: None

Created at: 12th May 2023 at 07:49

Contents

In-Silico Prediction

A majority rule based classifier that evaluates signal peptide (SP) predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome.

Obtain proteomes

No description specified

Signal Peptide Predictions

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Aspergillus niger centered protein clusters with a positive SignalP3 prediction

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  • SignalPeptidePrediction.XLS

Aspergillus niger CBS513.88 protein model verification of four selected proteins

No description specified

  • ProteinModelReannotation.DOC

Orthology identification

No description specified

GPI Anchor Predictions

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Metabolic model analysis

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Obtain metabolic model

No description specified

Identify enzymes from spectra

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Fingerprints

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MD5: e675ab854f5995cf3bbe43f64c728076

SHA1: 25789e5b1c3bce7f7b97529934e6ec0809a8a037

Citation
Andrabi, M. (2023). In-silico prediction and mass spectrometric validation of the Aspergillus niger secretome. IBISBAHub. https://doi.org/10.34701/IBISBA.1.INVESTIGATION.8.1
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Created: 12th May 2023 at 07:49

Last updated: 12th May 2023 at 07:51

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