Name: Dr. Zahra Pahlavan Yali
Type: User
Company: University of Mazandaran
Bio: Postdoctoral Researcher Chemometrics Laboratory, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
QSAR, Genomics, Deep learning
Location: Babolsar
Dr. Zahra Pahlavan Yali's Projects
AutoDock Vina
AstraZeneca add-ons to Orange.
Course materiale for intensive R course at Dept FOOD UPCH
BEAMSpy - Birmingham mEtabolite Annotation for Mass Spectrometry (Python Package)
Biobb (BioExcel building blocks) packages are Python building blocks that create new layer of compatibility and interoperability over popular bioinformatics tools.
Bioclipse Cheminformatics Feature
Utilities for building and managing bioconda recipes
A computational library for learning and evaluating biological knowledge graph embeddings
Automate the submission of jobs to the CABS-dock server for flexible protein-peptide docking
Python library for chemometric data analysis
CRAN Task View: Chemometrics and Computational Physics
Uses Generative approach for classification of wine.
Speed virtual screening by 50X
Deep Learning models applied to the analysis of VIS-NIR spectral data
Python implementation of domain-invariant partial least squares regression (di-PLS)
Python package for processing direct-infusion mass spectrometry-based metabolomics and lipidomics data
Galaxy tools for Python package DIMSpy: data processing of Direct-Infusion Mass Spectrometry-based metabolomics and lipidomics data
Docker container for DOCK6 molecular docking software
Docking Tutorial Using Autodock Vina version 1.2.3 (2021) and AutoDock-GPU Version 1.5.3
DockQ is a single continuous quality measure for protein docked models based on the CAPRI evaluation protocol
A Deep-learning based dOcking decoy eValuation mEthod
Detection and elimination of shadows in multi-spectral images (Do a literature review of shadow detection and removal with focus on multispectral images)
Emap2sec is a computational tool to identify protein secondary structures
FeatureSelect
A GUI for NIRS modelling of fruit (Especial methods to correct for batch effects)