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Web application and service for visualizing small- to medium-scale models of gene regulatory networks. It automatically lays out either an unweighted or weighted network graph based on an Excel input spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows. It is best-suited for visualizing networks of fewer than 35 nodes and 70 edges and has general applicability.

CalibraCurve is a computational tool designed to generate calibration curves for targeted mass spectrometry-based quantitative data. It is applicable to various omics disciplines, including proteomics, lipidomics, and metabolomics. The package also offers functionalities for data and calibration curve visualization and concentration prediction from new datasets based on the established curves.

From https://anndata.readthedocs.io/en/latest/ "Python package for handling annotated data matrices in memory and on disk, positioned between pandas and xarray."

Documentation Rectangle is an open-source Python package for single-cell-informed cell-type deconvolution of bulk and spatial transcriptomic data. Rectangle presents a novel approach to second-generation deconvolution, characterized by hierarchical signature building for fine-grained cell-type deconvolution, estimation and correction of unknown cellular content, and efficient handling of large-scale single-cell data during signature matrix computation. Rectangle was developed to overcome the current challenges in cell-type deconvolution, providing a robust and accurate methodology while ensuring a low computational profile.

DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.

Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data

Comprehensive set of programs for phylogenetic analyses; available for PC and Mac; source code available for easy compiling in UNIX.

zitools allows for zero inflated count data analysis by either using down-weighting of excess zeros or by replacing an appropriate proportion of excess zeros with NA. Through overloading frequently used statistical functions (such as mean, median, standard deviation), plotting functions (such as boxplots or heatmap) or differential abundance tests, it allows a wide range of downstream analyses for zero-inflated data in a less biased manner. This becomes applicable in the context of microbiome analyses, where the data is often overdispersed and zero-inflated, therefore making data analysis extremly challenging.