Objectives To evaluate the performance of large language models (LLMs) in risk of bias assessment and to examine whether prompt engineering improves their accuracy and alignment with expert reasoning.

This repository contains a Python implementation of the ENHANCE algorithm for denoising single-cell RNA-Seq data (Wagner et al., 2019). The R implementation can be found in a separate repository.

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Erik Steiger discusses the operational pain ...

Abstract: Dimensionality reduction methods are employed to decrease data dimensionality, either to enhance machine learning performance or to facilitate data visualization in two or three-dimensional ...

This Python program provides a comprehensive pipeline for processing ANNOVAR files, converting them into AnnData format, and generating UMAP visualizations along with various summary reports based on ...

To understand the importance of eIF4F components, we employed computational methods on large public datasets to investigate the impact of positive selection on eIF4F dysregulation in cancer. By ...

Astrocytes are important regulators of blood flow and play a key role in the response to injury and disease in the central nervous system (CNS). Despite having an understanding that structural changes ...

Reduced-dimension or spatial in situ scatter plots are widely employed in bioinformatics papers analyzing single-cell data to present phenomena or cell-conditions of interest in cell groups. When ...