Publications by authors named "Armin Soleymaniniya"

Machine learning (ML) and deep learning (DL) models for peptide property prediction such as Prosit have enabled the creation of high quality in silico reference libraries. These libraries are used in various applications, ranging from data-independent acquisition (DIA) data analysis to data-driven rescoring of search engine results. Here, we present Oktoberfest, an open source Python package of our spectral library generation and rescoring pipeline originally only available online via ProteomicsDB.

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Article Synopsis
  • * The research involved 968 participants, with genetic variants associated with body mass index (BMI) being analyzed; ultimately, five significant variants were identified.
  • * Two GRS models (weighted and unweighted) showed strong predictive power for obesity, with a mean curve area of around 70%, highlighting specific genetic variants like ADRB3 rs4994 and FTO rs9939609 as having a major impact on obesity risk.
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Root system architecture (RSA) is an important agronomic trait with vital roles in plant productivity under water stress conditions. A deep and branched root system may help plants to avoid water stress by enabling them to acquire more water and nutrient resources. Nevertheless, our knowledge of the genetics and molecular control mechanisms of RSA is still relatively limited.

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