Explore @soedinglab Open Source projects

Söding Lab (@soedinglab)

soedinglab

Stars
2,135
Global Org. Rank 9,039 (Top 3 %)
Registered over 10 years ago
Most used languages

C
28.6 %

C++
20.0 %

Python
20.0 %

HTML
11.4 %

Shell
8.6 %

Perl
2.9 %

Papyrus 2.9 %

TeX
2.9 %

Vue 2.9 %
Location 🇩🇪 Germany
Country Total Rank 795
Country Ranking

Papyrus 1

C
28

Vue 82

HTML
514

Perl
675

C++
676

Shell
800

TeX
1,004

Python
2,220

MMseqs2

MMseqs2: ultra fast and sensitive search and clustering suite

hh-suite

Remote protein homology detection suite.

metaeuk

MetaEuk - sensitive, high-throughput gene discovery and annotation for large-scale eukaryotic metagenomics

plass

sensitive and precise assembly of short sequencing reads

CCMpred

Protein Residue-Residue Contacts from Correlated Mutations predicted quickly and accurately.

MMseqs2-App

MMseqs2 app to run on your workstation or servers

WIsH

Predict prokaryotic host for phage metagenomic sequences

spacedust

Discovery of conserved gene clusters in multiple genomes

uniclust-pipeline

spacepharer

SpacePHARER CRISPR Spacer Phage-Host pAiRs findER

prosstt

PRObabilistic Simulations of ScRNA-seq Tree-like Topologies

CCMgen

pdbx

pdbx is a parser module in python for structures of the protein data bank in the mmcif format

BaMMmotif

Bayesian Markov Model motif discovery - An expectation maximization algorithm for the de novo discovery of enriched motifs as modelled by higher-order Markov models.

merlot

Reconstruct the lineage topology of a scRNA-seq differentiation dataset.

kClust

kClust is a fast and sensitive clustering method for the clustering of protein sequences. It is able to cluster large protein databases down to 20-30% sequence identity. kClust generates a clustering where each cluster is represented by its longest sequence (representative sequence).

b-lore

Bayesian multiple logistic regression for GWAS meta-analysis

MMseqs

BaMMmotif2

Bayesian Markov Model motif discovery tool version 2 - An expectation maximization algorithm for the de novo discovery of enriched motifs as modelled by higher-order Markov models.

ffindex_soedinglab

tejaas

Tejaas - a tool for discovering trans-eQTLs

bbcontacts

Prediction of beta-strand pairing from direct coupling patterns

hhdatabase_cif70

Scripts to generate the pdb70 database for hh-suite on the basis of pdb's mmcif format

PEnG-motif

PEnG-motif is an open-source software package for searching statistically overrepresented motifs (position specific weight matrices, PWMs) in a set of DNA sequences.

transannot

TransAnnot - a fast transcriptome annotation pipeline

BaMM_webserver

Webserver for motif discovery with higher-order Bayesian Markov Models (BaMMs)

metaG-ECCB18-partII

MMseqs2 tutorial for metagenomics sequence data

bamm-suite

De-novo motif discovery and optimization

CCMgen-scripts

Contains plotting scripts, examples, and other small scripts relevant to CCMgen and the corresponding publication.

mockinbird

PAR-CLIP data processing pipeline

bipartite_motif_finder

BMF: Bipartite Motif Finder

CoCo

Consensus Correction

MMseqs2-Regression

MMseqs2 Regression Testing

xxmotif

XXmotif: eXhaustive, weight matriX-based motif discovery in nucleotide sequences

prosstt-r

An R package with evaluation and visualization functions for the python PROSSTT package