Improved Understanding and Predictability of Peptide Response in Bottom-Up Proteomics Through Deep Learning: A Data-Centric Approach Towards Absolute Peptide Quantification, Extracting Meaningful Information and Building Predictive Models from Mass Spectrometric Data

Naim Abdul Khalek Gharzeddine

doi:10.54337/aau750215857

Improved Understanding and Predictability of Peptide Response in Bottom-Up Proteomics Through Deep Learning: A Data-Centric Approach Towards Absolute Peptide Quantification, Extracting Meaningful Information and Building Predictive Models from Mass Spectrometric Data

Publikation: Ph.d.-afhandling

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Originalsprog	Engelsk
Vejledere	Wimmer, Reinhard, Hovedvejleder Gregersen, Simon, Bivejleder
Udgiver	Aalborg University Open Publishing
ISBN'er, elektronisk	978-87-94563-95-6
DOI	https://doi.org/10.54337/aau750215857
Status	Udgivet - 2024

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10.54337/aau750215857

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Citationsformater

Abdul Khalek Gharzeddine, N. (2024). Improved Understanding and Predictability of Peptide Response in Bottom-Up Proteomics Through Deep Learning: A Data-Centric Approach Towards Absolute Peptide Quantification, Extracting Meaningful Information and Building Predictive Models from Mass Spectrometric Data. Aalborg University Open Publishing. https://doi.org/10.54337/aau750215857

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Improved Understanding and Predictability of Peptide Response in Bottom-Up Proteomics Through Deep Learning: A Data-Centric Approach Towards Absolute Peptide Quantification, Extracting Meaningful Information and Building Predictive Models from Mass Spectrometric Data. / Abdul Khalek Gharzeddine, Naim.
Aalborg University Open Publishing, 2024. 246 s.

Publikation: Ph.d.-afhandling

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Abdul Khalek Gharzeddine N. Improved Understanding and Predictability of Peptide Response in Bottom-Up Proteomics Through Deep Learning: A Data-Centric Approach Towards Absolute Peptide Quantification, Extracting Meaningful Information and Building Predictive Models from Mass Spectrometric Data. Aalborg University Open Publishing, 2024. 246 s. doi: 10.54337/aau750215857