Scientific Computing @ Max-Planck-Institute for Evolutionary Biology's repositories
GenomeFeatureFormatOntology
An ontology to represent genome feature annotations in gff3 format.
misic
segmentation of rod-shaped bacteria
MultiNEAT
Portable NeuroEvolution Library
2023-04-04-MPIEvolBio
Workshop repository for the Software Carpentry Workshop "Unix, Git, Programming and Plotting with Python" at MPI Evolutionary Biology
bioconda-recipes
Conda recipes for the bioconda channel.
chado-LD
Linked data representations of the chado database schema
DeLTA_doc
Documentation Retraining DeLTA 2.0
diffexpr
Porting DESeq2 and DEXSeq into python via rpy2
DLSegBench
Benchmarking deep learning based cell segmentation
dm-workshop2021
Material for the Data Management Workshop at MPI Evolutionary Biology May 17-18 2021
FakeData
Detection of fabricated/falsified data using Brenford's law
gffpandas
Parse GFF3 into Pandas dataframes
ImgSeg-Tools
Helpful information about several image segmentation tools. Installation, usage, parameters
machado
This repository provides users with a framework to store, search and visualize biological data.
Magritte
A modern software library for simulating radiation transport.
OBIS-CC
Community contributions to the OpenBIS ELN/LIMS ecosystem
omero-scripts
Core OMERO Scripts
PyFPT
Stochastic first-passage time (FPT) simulations using importance sampling.
python-novice-inflammation
Programming with Python
PyTripalSerializer
Serialize Tripal's JSON-LD API into RDF format
quickstatements_client
A data model and client for QuickStatements (for Wikidata)
REALPHY
REALPHY - The Reference sequence Alignment based Phylogeny builder is a free online pipeline that can infer phylogenetic trees from whole genome sequence data. The user only has to provide a small number of reference genomes in either FASTA or Genbank format (contigs or fully sequenced genomes) as well as a number of other query genomes which can be in FASTQ (short reads), FASTA or Genbank format. All provided sequences (references and queries) will then be mapped to each of the references via bowtie2. From these alignments multiple sequence alignments will be reconstructed from which phylogenetic trees are inferred via PhyML. The alignments, tree files and information on SNPs and deleted sites will be available for download after the program has finished. Furthermore the user has the option to combine individual reference alignments by ticking the merge box. This will combine different reference genome alignments and hence increase the quality of the inferred phylogeny. However, this option is very time and RAM intensive.
Tensorflow-Neuroevolution
Neuroevolution Framework for Tensorflow 2.x focusing on modularity and high-performance. Preimplements NEAT, DeepNEAT, CoDeepNEAT, etc.