Tools used in implementing the RNN models. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Implementation of the SAACS in python. حسب Pavel Škrabánek (6106427)

Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management حسب Pavel Izosimov (20096259)

"…</li><li><b>Source Code Protection</b>: Implement multi-level <b>source code protection</b> with dynamic <b>code obfuscation in Python</b>, making it significantly harder for others to reverse-engineer your code.…"

Summary of search process from different digital libraries. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Table_1_An application programming interface implementing Bayesian approaches for evaluating effect of time-varying treatment with R and Python.pdf حسب Chen Chen (6544)

"…The examples demonstrate the use of the API calling from R and Python, for handling both non-adaptive or adaptive treatments, with presences of partially observed or missing data issues. …"

Python implementation of a wildfire propagation example using m:n-CAk over Z and R. حسب Pau Fonseca i Casas (9507338)

Python sript. حسب Kan Jia (6438599)

Analysis of the selected studies in terms of tools used for implementing RNN models. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

PYTHON حسب Kan Jia (21666161)

Hardware parameters of optimal implementations. حسب Xuzhen He (14676114)

الموضوعات:

Average of F1-score across years. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Research questions and main motivations. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Data extraction template. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Overview of systematic literature review. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Study selection process. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Average F-score across years. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

The final selected studies. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Quality assessment criteria. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Selected online databases. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data حسب Anthony S. Barente (14035175)

"…Here we describe pyAscore, an efficient and versatile implementation of the Ascore algorithm in Python for scoring the localization of user defined PTMs in data dependent mass spectrometry. pyAscore can be used from the command line or imported into Python scripts and accepts standard file formats from popular software tools used in bottom-up proteomics. …"