YOUR BENEFITS USING TRANSFAC 2.0

MOTIFS AND PREDICTION OF TF-BINDING SITES

Use the most comprehensive library of known eukaryotic transcription factor binding motifs

TRANSFAC systematically collects all available TF-binding motifs in the form of Positional Weight Matrices (PWMs) from scientific literature and repositories, as well as PWMs constructed by the TRANSFAC team on the basis of experimentally verified TF binding sites. Currently TRANSFAC provides more than 10,000 PWMs for various eukaryotic taxonomic groups. Our goal is to provide the most comprehensive resource of TF binding motifs for researchers world-wide

Identify common motifs in a set of target DNA sequences

Determine common motifs and compare these de-novo motifs to known transcription factor DNA binding site consensus sequences present in the TRANSFAC database

Detect genomic variants affecting TF-binding sites

Analyze mutations from your NGS data in regulatory regions for their potential negative or positive effect on transcription factor binding

Predict TF-binding sites in eukaryotic DNA sequences

Our tools predict transcription factor (TF) binding sites and composite regulatory regions using Machine Learning (ML) and Artificial Intelligence (AI)

PROMOTERS AND ENHANCERS

The unrivaled resource for studying promoters and enhancers

Due to its comprehensive data on transcription factors and their binding sites, tools for motif analysis, support for cross-species comparisons and functional annotations, TRANSFAC is an indispensable resource for studying promoters and enhancers

Find known transcriptional regulators for your gene(s) of interest

Search for factor-gene interactions in TRANSFAC, the largest collection of published experimentally proven transcription factor binding sites

Explore factor-factor interactions and composite elements

Complement the unparalleled collection of factor-gene interactions with factor-factor interactions and synergistic and antagonistic composite elements

Predict target genes

Find target genes for a transcription factor of interest by studying from single gene promoters to whole genomes

Analyze genes for tissue- and GO-specific transcription factors

Select tissue- / cell type- / induction-specific transcription factors for genes from human and model organisms

PATHWAYS AND MASTER REGULATORS

Identify pathways up- and down-stream of a gene (set)

Explore activation patterns of genes in tissues and cells of your interest and build complex interaction networks based on individual reactions with experimental details, protein-protein interactions (PPIs) and post-translational modifications (PTMs) in TRANSFAC PATHWAYS

Apply integrated network analysis and visualization

Profit from the combined approach towards causative gene regulation studies. Explore activation patterns of genes in tissues and cells of your interest and build complex interaction networks with identified master regulators

Map gene sets on pathways

Draw insights on biological function of your gene set by mapping them on pathways

Customize regulatory and metabolic networks

Build networks based on more than one million reactions extracted from original scientific literature and evaluated by experts.

MULTI-OMICS

Easily process and integrate all your omics data with TRANSFAC PATHWAYS / DISEASES

Preprocess, functionally explore, and unite various omics data (genomics, transcriptomics, metabolomics, proteomics and epigenomics) in a fully automized pipeline and get a combined and integrated report

Find common functional properties in a set of (co-regulated) genes

Map your data on various ontologies and identify overrepresented functional assignments in your gene set

Compare and functionally align your data

Observe how your omics data sets (genomics, transcriptomics, proteomics, epigenomics or metabolomics) correlate between each other

Utilize upstream analysis

Benefit from our unique upstream analysis approach combining promoter and pathway analysis to identify transcription factors and upstream master regulators (as potential drug targets) which can explain expression changes of your DEGs (or other changes in gene or protein signatures)

BIOMARKERS, DRUGS AND COMPOUNDS

Discover disease molecular mechanisms

Make use of the vast amount of gene-disease and gene-drug assignments and identify novel biomarkers and drug targets

Reconstruct disease molecular mechanism

Understand the drug’s mechanism of action (MoA) based on the collected omics data

Trace back the activated pathways

Detect disease master regulators, responsible for governing the pathology development processes, and therapeutic targets

PRECISION MEDICINE

Employ personalized medicine with TRANSFAC DISEASES

With our fully automated pipeline for patient’s multi-omics data analysis TRANSFAC DISEASES generates a comprehensive report about the personalized drug targets identified for a certain patient, or a group of patients, and the potentially effective drugs. Application examples include cancer, neurodegenerative diseases, infectious diseases, diabetes, metabolic diseases and hypertension

Develop a personalized therapy

Identify individual drug targets and corresponding treatments based on the pathology molecular mechanism reconstructed on omics data collected from a particular patient

Repurpose drugs

Explore how known drug targets can be activated in various pathologies. Check out the possible off-label usage of treatments and identify prospective drug combinations for better patient outcomes

Find new drug candidates

Identify novel drug targets and find prospective drug-like compounds potentially acting on them by using integrated promoter, pathway and cheminformatics analysis

GENERAL

Inbuilt workflows

Make use of over 200 pre-compiled workflows

Customizable pipelines

Construct your own dedicated analysis pipeline with visual programming

Integrated Genome Browser

Get your result in tabular format as well as in the integrated genome browser

Application Programming Interface (API)

Use Java-based API, R-based API or Jupiter notebook

Pathway/Network visualization

Visualize canonical pathways and analysis-dependent networks

Comprehensive analysis reports

Profit from automatically generated analysis reports including network visualizations, functional annotation diagrams and more

WHAT MAKES TRANSFAC 2.0 DIFFERENT FROM OTHER TOOLS?

Most comprehensive database on gene regulation 

TRANSFAC stands as the pioneering and most comprehensive database on eukaryotic transcription factors (TFs), their genomic binding sites (TFBS), and DNA binding profiles (PWMs).

35 years of curation and maintenance

Once established over 35 years ago, TRANSFAC has been diligently maintained and manually curated ever since.

The biggest collection of experimentally proven functional TF binding sites

TRANSFAC 2.0 contains the biggest collection of experimentally proven TF binding sites that regulate expression of genes in genomes of eukaryotic organisms curated from original publications and documented with detailed information about tissue, cell types, TF source and quality of experimental evidence.   

The largest library of Positional Weight Matrices (PWMs)

TRANSFAC 2.0 contains over 10,000 DNA binding patterns in the format of positional weight matrices (PWMs) for animals, plants and fungi. PWMs are built based on experimentally proven TF binding sites, curated from original scientific publications and integrated from other databases.

Signal transduction network of more than 1,200,000 reactions 

TFs are connected to a network of more than 1,200,000 of signal transduction and metabolic reactions extracted from original scientific literature and evaluated by experts. Over 1500 canonical pathways are described based on these reactions.   

Unique algorithm to find master-regulators 

Master-regulators are discovered by the “upstream analysis” that uniquely integrates promoter and network analysis using graph search and genetic algorithms.

Biggest collection of more than 140,000 disease biomarkers 

Manually curated collection of more than 140,000 gene to disease associations as correlative, causal and disease mechanisms biomarkers and drug targets.

Reconstruction of disease molecular mechanisms based on the upstream analysis 

Combining upstream analysis approach and disease and pathway information allows to reconstruct disease mechanisms and find novel drug targets.

Over 300 powerful tools and pipelines to study gene regulation 

TRANSFAC 2.0 provides a platform of multiple web tools and ready pipelines for  analysis of NGS, RNA-seq, ChIP-seq, ATAC-seq, CUT&RUN and other types of genomics, transcriptomics, epigenomics, proteomics and metabolomics data. No cumbersome installation or special bioinformatics skills are needed.   

Robust AI algorithms for promoter and enhancer analysis 

Integration of powerful tools for scanning genomes for TF binding sites and for discovering site enrichment and site combinatorial modules using AI, such as genetic algorithms,  and machine learning.

Automatic multi-omics discovery pipeline “Genome Enhancer”

Genome Enhancer provides a fully automated pipeline, including report, for patient omics data analysis, which identifies prospective drug targets and corresponding treatments by reconstructing the molecular mechanism of the studied pathology.