A complete end-to-end pipeline integrating paired scRNA-seq and scATAC-seq data (10x Multiome, SHARE-seq, SNARE-seq) using scGLUE and MOFA+, with automatic cell type annotation and gene regulatory ...

When it comes to working with data in a tabular form, most people reach for a spreadsheet. That’s not a bad choice: Microsoft Excel and similar programs are familiar and loaded with functionality for ...

A while ago, I was asked by a former colleague about the best way to convert Parquet files into comma-separated values (CSV) format using Python. The honest answer? It depends. And so on and so on ...

Evaluate the effectiveness of Microsoft’s Python Risk Identification Toolkit (PyRIT) for agentic AI red teaming. Address evolving autonomous AI system threats.

Reliable data on residential power generation and consumption is vital for effectively integrating renewable energy sources. This is particularly important in the Baltic countries, where climate ...

Assessment and monitoring of surface water quality are essential for food security, public health, and ecosystem protection. Although water quality monitoring is a known phenomenon, little effort has ...

Effectively identifying and managing missing data is vital for accurate data analysis and model performance. Handling missing values in Python Pandas is crucial for preparing datasets for analysis.

Data analysis is an integral part of modern data-driven decision-making, encompassing a broad array of techniques and tools to process, visualize, and interpret data. Python, a versatile programming ...

Databases used for clinical interpretation in oncology rely on genetic data derived primarily from patients of European ancestry, leading to biases in cancer genetics research and clinical practice.

If you have ever done any kind of experimenting in data science, you must have heard of Pandas. To quote the corresponding Github documentation, Pandas is a “Flexible and powerful data analysis / ...