Issar Arab

Improved open modification searching via unified spectral search with predicted libraries and enhanced vector representations in ANN-SoLo

The paper enhances ANN-SoLo for open modification searching by integrating predicted spectral libraries and improved vector representations, improving peptide identification in complex proteomics workflows.

Semi-Supervised Learning to Boost Cardiotoxicity Prediction by Mining a Large Unlabeled Small Molecule Dataset

This study uses semi-supervised learning on a large unlabeled dataset to improve cardiotoxicity prediction for three ion channels, identifying potential cardiac-active compounds.

Semi-supervised machine learning for sensitive open modification spectral library searching

This paper integrates semi-supervised machine learning into the ANN-SoLo tool to improve spectral library searching for open modification peptides, increasing identification rates.

IsarPipeline: Combining MMseqs2 and PSI-BLAST to Quickly Generate Extensive Protein Sequence Alignment Profiles

The paper introduces IsarPipeline, a hybrid tool combining MMseqs2 and PSI-BLAST to rapidly generate protein sequence alignment profiles, significantly faster than PSI-BLAST alone.