Search Results for "alignment"

pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. pandas is continuously being developed to be a fundamental high-level building...

...Datachain can persist features of Python objects returned by AI models, and enables vectorized analytical operations over them. The typical use cases are data curation, LLM analytics and validation, image segmentation, pose detection, and GenAI alignment. Datachain is especially helpful if batch operations can be optimized – for instance, when synchronous API calls can be parallelized or where an LLM API offers batch processing.

...They can be organized in categories and each category has a color. Images, checkboxes and a few predefined symbols can be inserted in the notes. The style of the text can be changed (alignment, style, color).

PyTom is a toolbox developed for interpreting cryo electron tomography data. All steps from reconstruction, localization, alignment and classification are covered with standard and improved methods. Please sign up to our mailing list to keep up with the most recent updates and versions.

ADOMA stands for: Alternative Display Of Multiple Alignment. ADOMA can create four different displays of a multiple sequence alignment: a ClustalW alignment in HTML format, a simplified ClustalW alignment in HTML and/or txt format and a colored ClustalW alignment in HTML format. For examples of these outputfiles check the screenshots. ADOMA uses ClustalW to create the multiple alignment from DNA or protein sequences and displays them slightly different than the normal output of ClustalW. ...

COV2HTML provides an easy and 'in home' web interface for biologists that allows coverage visualization of the NGS alignment needed for the analysis. It combines two essential processes: (i) MAP2COV, a tool that converts the huge NGS mapping or coverage files into light specific coverage files which contains genetic elements informations. (ii) COV2HTML, a visualization interface allowing a real-time analysis of data with selected criteria. Thus this interface offers a visualization of NGS mapping coverage data (DNA-seq, RNA-seq, ChIP-seq and TSS) performed in different prokaryotic organisms (bacteria, viruses...) or different experimental conditions (mutant versus wild type strains or different growth states…) facilitating studies.