sPLINK (safe PLINK) allows the federated, privacy-preserving analysis of GWAS data. It works on distributed datasets without exchanging raw data and is robust against imbalanced phenotype distributions across cohorts. Federated and user-friendly analysis with sPLINK, thus, has the potential to replace meta-analysis as the gold standard for collaborative GWAS. 

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Flimma is the federated implementation of the popular differential expression analysis workflow limma voom. Flimma provides several advantages over the existing approaches for gene expression analysis. Unlike limma voom, Flimma by design preserves the privacy of the data in the cohorts since the expression profiles never leave the local execution sites. In contrast to meta-analysis approaches, Flimma is particularly robust against heterogeneous distributions of data across the different cohorts, which makes it a powerful alternative for multi-center studies where patient privacy matters.

DiNiro can uncover novel and relevant mechanistic models that not only predict but also explain differential cellular gene expression programs. These mechanisms can be presented as small, easily interpretable transcriptional regulatory network modules. Start exploring the possibilities of scRNA-seq technology with DiNiro today and unlock a new level of understanding in gene function and disease mechanisms. 

NeDRex is an interactive network medicine platform for disease module identification and drug repurposing. It is build of three main components: a knowledgebase (NeDRexDB), a Cytoscape app (NeDRexApp), and an API (NeDRexAPI).

NeDRex integrates different data sources covering genes, drugs, drug targets, disease annotations, and their relationships. It allows for constructing heterogeneous biological networks, mining them for disease modules, prioritizing drugs targeting disease mechanisms, and statistical validation. The utility of NeDRex is shown with five specific use-cases in the paper (download from Nature).

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CADDIE is a web application for drug repurposing in cancer integrating six human gene-gene and four drug-gene interaction databases, information regarding cancer driver genes, cancer-type specific mutation frequencies, gene expression information, genetically related diseases, and anticancer drugs. The website offers access to various network algorithms for identifying drug targets and drug repurposing candidates. It guides users from the selection of seed genes to the identification of therapeutic targets or drug candidates, making network medicine algorithms accessible for clinical research.

Scellnetor is a novel clustering tool for scRNA-seq data that takes Scanpy generated AnnData objects in H5AD file-format as input. With Scellnetor you can compare two sets of cells that you manually select on one of your Scanpy-generated plots. The output will be connected components of genes where the genes are either differently or similarly expressed in the two sets. You can also do a clustering of a single set, where the genes in the connected components are similarly expressed. For every cluster, you get a plot showing mean gene expression and the genes' 95 % confidence intervals and a table with statistically significant GO-terms.

With the DeepCLIP online tool you can choose one or more trained state-of-the-art performing models and use them to generate predictions and binding profiles of RNA-sequences of interest. Both predictions and binding profiles can detect how mutations may change the affinity of RNA-binding proteins for analyzed sequences.

Biclustering constrained by networks (BiCoN) is a powerful new systems medicine tool to stratify patients while elucidating disease mechanisms. BiCoN is a network-constrained biclustering approach which restricts biclusters to functionally related genes connected in molecular interaction networks and maximizes the expression difference between two groups of patients.

DIGGER is an essential resource for studying the mechanistic consequences of alternative splicing such as isoform-specific interaction and consequence of exon skipping. The database integrates information of domain-domain and protein-protein interactions with residue-level interaction evidence from co-resolved structures. DIGGER allows users to seamlessly switch between isoform and exon-centric views of the interactome and to extract sub-networks of relevant isoforms (isoforms specific PPIs).

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NEASE is a network-based approach for exon set enrichment. The python package NEASE  first detects protein features affected by AS such as domains, motifs and residues. Next, NEASE uses a protein-protein interactions integrated with domain-domain interactions, residue-level and domain-motif interactions to identify interaction partners and patways likely affected by AS.

Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. It was first identified in Wuhan, China, and has since spread causing a global pandemic. Various studies have been performed to understand the molecular mechanisms of viral infection for predicting drug repurposing candidates. However, such information is spread across many publications and it is very time-consuming to access, integrate, explore, and exploit. We developed CoVex, the first interactive online platform for SARS-CoV-2 and SARS-CoV-1 host interactome exploration and drug (target) identification. CoVex integrates 1) experimentally validated virus-human protein interactions, 2) human protein-protein interactions and 3) drug-target interactions. The web interface allows user-friendly visual exploration of the virus-host interactome and implements systems medicine algorithms for network-based prediction of drugs. Thus, CoVex is an important resource, not only to understand the molecular mechanisms involved in SARS-CoV-2 and SARS-CoV-1 pathogenicity, but also in clinical research for the identification and prioritization of candidate therapeutics. CoVex renders COVID-19 drug research systems-medicine-ready by giving the scientific community direct access to network medicine algorithms integrating virus-host-drug interactions. We documented the CoVex development in our publication (download from Nature).

GrandForest is an online tool for de novo endophenotyping and mechanotyping of diseases using omics data. PathClass is an online tool for breast cancer subtyping from gene expression data. Instead of using gene panels, we employ pathway activity patterns for this purpose, which render statistically way more robust. Our web application allows to predict breast cancer subtypes for new samples, including custom uploaded samples as well as samples found on the Gene Expression Omnibus. Furthermore, selected pathways used for the individual predictors can be investigated.

ROBUST is a Python tool which uses enumeration of diverse prize-collecting Steiner trees to compute disease modules that are robust to random bias.

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KeyPathwayMiner is a software for de novo network enrichment, aka network modules. It combines multiple OMICS data sets with biological networks to turn your expression, mutation, or association study into a systems biology story. It comes as Cytoscape app, as standalone software and as web service. It was downloaded >5000x from the Cytoscape app store alone and applied in various different biomedical settings.

TiCoNE is a software for the analysis of time course expression data (e.g. gene expression) together with biological networks. It will find time patterns emerging in the expression data and check for network modules enriched with genes of similar expression behavior over time. It comes as web server and as Cytoscape plugin.

Genes carry binding sites that allows specific microRNAs to repress their expression. According to the competing endogenous RNA hypothesis, genes also regulate each other in a competitive fashion via sponging microRNAs. We have contributed to the development of the (partial) correlation-based method SPONGE and the (conditional) mutual information-based method JAMI to infer such microRNA-mediated gene-gene interactions. In particular SPONGE is fast enough to infer ceRNA interactions genome-wide and thus facilitates the inference of a ceRNA regulatory network that can be used for hypothesis generation, biomarker detection and drug target discovery.

DiMmer is a Java tool for efficient processing of Illumina 450K and 850K EPIC chip data. It is fully parallelizable and can process even big cohort data sets. With DiMmer, one may now even compute empirical p-values using permutation tests and find differentially methylated regions including different strategies for correction for multiple testing. It can correct for cell composition effects and other confounders. Continuous outcome variables and confounders can be directly integrated using regression models. It comes with an intuitive user interface that guides the clinician or biologist through all steps of a typical Illumina EWAS chip data analysis.

CoNVaQ is a web service for CNV-based association study between two or more sample groups. The web interface allows one to quickly upload segmented CNV samples and search for variations that are overrepresented in a population. CoNVaQ differs from previous tools by allowing you to specify which CNVRs are considered significant using simple queries, e.g. “find the largest region duplicated in > 70% of cases and < 10% of controls”.

BioAtlas is a novel user-friendly platform to ease ecologists in accessing the power of microbial 16S rRNA profiling in a location-specific context. The BioAtlas web interface allows several kinds of interactive analyses: 1) Browsing the geographical distribution of microbial taxonomies across the planet in google maps, 2) across the human body, and 3) across user-defined maps and using taxonomic trees. 4) Browsing the distribution of the occurring taxonomies in user data against previously discovered

taxonomies across the planet, the human body, and/or own user maps. 6) Building own user maps (e.g. for plants, animals, …) online and mapping of taxonomies to the locations, and follow-up comparison of additional samples and taxonomy distributions with these maps.

HitSeekR is the first web platform for analyzing high-throughput screening (HTS) data of various types, from miRNA (inhibitor) screens and RNAi assays to CRISPER/cas9 and drug response screens. It can accommodate, normalize, etc. small to ultra-large scale, and it turns your HTS data into a systems biology story.

BALSAM is a comprehensive web-platform to simplify and automate the analysis and discovery of metabolite patterns in Multi-Capillary-Column Ion-Mobility-Spectrometry data. It combines preprocessing, peak detection, feature extraction, visualization and pattern discovery.

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MIMA is a method for the alignment of GC/MS data and MCC/IMS data facilitating the identification of biomarker molecules.

IMSDB is database system and machine learning user interface for biomarker mining and identification in breath data from GC/MS and MCC/IMS data sets.

Carotta is a method for the identification of hidden confounding factors in breath data.

Transitivity Clustering is a tool for solving the Weighted Graph Cluster Editing Problem using a force-based heuristic. It comes with several extensions. TransClustMV, for instance, works with missing values.

ClustEval is a platform for the evaluation of clustering tools in many different biomedical settings.

BiCluE is a software for weighted bi-cluster editing. It can be applied to identify groups of phenotypes that are associated with sets of genotypes (sampled from e.g. GWAS data).

BiForce is an extension of BiCLuE. It was applied to bi-cluster gene expression data sets to find sets of genes correlating with sets of conditions.

GEDEVO is a method for pairwise network (graph) alignment using optimizing a global criterion: minimal graph edit distance, i.e. the minimal number of node/edge additions/deletions to transform one graph into another one. GEDEVO-M is an extension of GEDEVO for the alignment of multiple (>2) input networks. And NABEECO solves network alignment using Bee Colony Optimization.

CytoGEDEVO is a Cytoscape implementation of the pairwise network alignment algorithm of GEDEVO, which allows the direct integration of external node similarities (e.g. BLAST or graphlets).

CoryneRegNet is the international reference database for corynebacterial transcriptional gene regulatory interactions.

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EhecRegNet is a database of gene regulations conserved between E. coli K12 and human pathogenic EHEC strains.

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PetriScape is a tool for discrete Petri net simulation of biological networks in Cytoscape.

LiSSI is a java tool for predicting life-style-specific genomic islands through evolutionary conservation. It is divided into three sequentially executed modules: evolutionary sequence analysis, island detection, and machine learning.

PIPS is a tool specifically for the prediction of pathogenicity islands using sequence features.

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GIPSy extends on the PIPS idea and implements a software for using genomic features to predict pathogenicity islands as well metabolic and resistance islands in bacterial genomes.

MIRACLE is an online platform for microarray R-based analysis of complex lysate experiments. It is bridging the gap between spotting and array analysis by conveniently keeping track of sample information. Data processing includes correction of staining bias, estimation of protein concentration from response curves, normalization for total protein amount per sample and statistical evaluation.

OpenLabFramework with its extension OpenLabNotes is an open-source laboratory information management system (LIMS) intended for advanced sample management in small to mid-sized laboratories. It has been developed with focus on the management of vector clone and genetically engineered cell lines.