Scorecard Development in python, 评分卡

Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual explanations.

Assembly and binning of metagenomes

Scorecard Development in R, 评分卡

Nature Communications | BASALT (Binning Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencing data

Find nearby 3D objects in constant time O(1).

A hybrid assembly and MAG recovery pipeline (and more!)

✨🧬 Refined binning of metagenomic contigs using assembly graphs

🚦🧬 Binning Metagenomic Contigs via Composition, Coverage and Assembly Graphs

A fast and space-efficient pre-filter for querying very large collections of nucleotide sequences.

An algorithm for creating user configurable, variable-precision sliding windows of time. Useful for binning time values in large collections of data.

Autometa: Automated Extraction of Genomes from Shotgun Metagenomes

pure Julia package for optimal histogram binning, based on piecewise constant model.

A Community Tool for Transiting Exoplanet Science with the JWST & HST

☯️🧬 Refined and Overlapped Binning of Metagenomic Contigs Using Assembly Graphs

AMBER: Assessment of Metagenome BinnERs

BinaRena: Interactive Visualization and Binning of Metagenomic Contigs

Improving genome bins through the combination of different binning programs

Statistical standard error estimation tools for correlated data

Rapid and simple taxonomic profiling of genome and metagenome contigs

Bayesian histograms for estimation of binary rare event rates, with fully automated bin pruning :bar_chart:

Repository of our application for human-augmented binning

No description provided.

Reference-free Binning of Metagenomics Long Reads using Coverage and Composition

BinGuru is an open-source Typescript package to bin/classify data using 18 established binning methods, including a new method, resiliency.

Binnacle: Using Scaffolds to Improve the Contiguity and Quality of Metagenomic Bins

Tools for binning data

Contains our Approach for the competition organized at Udyam'21

Implementation of Data Preprocessing techniques such as handling missing values, noise smoothing, PCA, etc.

REcovery of eukaryotic genomes using contrastive learning. A specialized metagenomic binning tool designed for recovering high-quality eukaryotic genomes from mixed prokaryotic-eukaryotic samples.