DIANA LAB (c) 2008
   
 
Back to the HomepageSection containing the software developed by the DIANA LabSection containing access to tools for manipulating databases developed by the DIANA LabInformation of the current DIANA Lab membersKey publications from the DIANA LabSoftware and database tool help
 
 
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  WELCOME TO THE DIANA LAB WEBPAGE

Lab Intro
Computational predictive models are a key element of current systems biology. The focus of the DIANA lab is on the development of algorithms, databases and tools for interpreting and archiving genomic data in the framework of a systemic analysis. Current emphasis is on the analysis of microRNA (miRNA) and protein coding genes. MiRNAs are recently identified to be very abundant in mammalian organisms and play a key role in regulating development.

Comprehensive models work and integrate data at various levels of biological detail. Therefore the activities of the DIANA lab range from the analysis of expression regulation from deep sequencing data, the annotation of miRNA regulatory elements and targets to the interpretation of the role of miRNAs in various diseases.

Currently active projects of the DIANA-lab group include:

MicroRNA target prediction
DIANA-microT-CDS (v5.0): DIANA-microT-CDS is the 5th version of the microT algorithm. It is specifically trained on a positive and a negative set of miRNA Recognition Elements (MREs) located in both the 3'-UTR and CDS regions. DIANA-microT-CDS provides a significant increase in sensitivity compared to the previous version (65% vs 52%), when compared against experimental proteomics data. It exhibited the highest sensitivity at any level of specificity, when compared against other state of the art implementations. DIANA-microT-CDS has been updated (July 2012) to miRBase 18 and is fully compatible with the new miRNA nomenclature introduced in this version. It also provides hyperlinks to on-line servers such as iHOP and expression data for the selected microRNAs in tissues and cell lines. Furthermore, microT-CDS users can examine the species where each binding site is conserved, filter results using score thresholds or by restricting the algorithm on genes belonging to specific KEGG pathways. DIANA-microT-CDS can be accessed from the following address: http://www.microrna.gr/microT-CDS.

 

Analysis of expression data for microRNA function
DIANA-mirExTra is an algorithm that can identify microRNA effects to the Expression levels of protein-coding Transcripts, based on the frequency of six nucleotide long motifs (hexamers) in the 3'UTR sequences of genes. Additional features include the combination of multiple hexamers corresponding to the same microRNA sequence, use of evolutionary conservation between human and mouse to increase robustness and correction of microarray data for single nucleotide compositional bias. Direct links to further functional analysis of produced results based on DIANA-mirPath are provided for all results. DIANA-mirExTra can be accessed from the following address: http://diana.cslab.ece.ntua.gr/hexamers.

 

Incorporating microRNAs in pathways
DIANA-miRPath v2.0 is the new version of DIANA-miRPath web server, which was redesigned from the ground-up. The user of DNA Intelligent Analysis (DIANA) DIANA-miRPath v2.0 can now utilize miRNA targets predicted with high accuracy based on DIANA-microT-CDS and/or experimentally verified targets from TarBase v6; combine results with merging and meta-analysis algorithms; perform hierarchical clustering of miRNAs and pathways based on their interaction levels; as well as elaborate sophisticated visualizations, such as dendrograms or miRNA versus pathway heat maps, from an intuitive and easy to use web interface. New modules enable DIANA-miRPath server to provide information regarding pathogenic single nucleotide polymorphisms (SNPs) in miRNA target sites (SNPs module) or to annotate all the predicted and experimentally validated miRNA targets in a selected molecular pathway (Reverse Search module). DIANA-miRPath v2.0 is an efficient and yet easy to use tool that can be incorporated successfully into miRNA-related analysis pipelines. DIANA-miRPath v2.0 can be accessed from the following address: http://www.microrna.gr/miRPathv2.

 

Database of experimentally supported microRNA targets
TarBase 6.0 is the largest available manually curated target database, indexing more than 65,000 miRNA-gene interactions, 16.5-175-fold more than any other available implementation. The database includes targets derived from specific, as well as high throughput experiments, such as microarrays and proteomics. Specific attention was paid in the inclusion of targets derived from sequencing experiments, such as HITS-CLIP and PAR-CLIP. TarBase hosts data derived from 3 CLIP-Seq and 12 Degradome-Seq studies, significantly more than any other available database. The database is seamlessly interconnected with other DIANA-lab tools, such as DIANA-microT, enabling it to extend each validated interaction with in silico predicted information. DIANA-TarBase offers a significant amount of crucial information to the user, including detailed description of the involved genes and miRNAs, a list of publications supporting each interaction, the experimental methods used for validations along with their outcomes. The database provides also links to related KEGG pathways, as well as to other external databases such as Ensembl, Uniprot and RefSeq. It is also equipped with powerful searching and filtering capabilities. TarBase 6 users can directly extend the database by submitting data derived from their publications. Currently (as of August 2012), the TarBase 6.0 dataset is freely available for download. DIANA-TarBase 6.0 can be accessed from the following address: http://www.microrna.gr/tarbase.

 
     
     
  LATEST LAB PUBLICATIONS

Vlachos IS, Kostoulas N, Vergoulis T, Georgakilas G, Reczko M, Maragkakis M, Paraskevopoulou MD, Prionidis K, Dalamagas T, Hatzigeorgiou AG (2012) DIANA miRPath v.2.0: investigating the combinatorial effect of microRNAs in pathways., Nucleic Acids Res. ,40(W1) ,W498-W504. PubMed

Reczko M, Maragkakis M, Alexiou P, Papadopoulos GL, Hatzigeorgiou AG. (2012) Accurate microRNA Target Prediction Using Detailed Binding Site Accessibility and Machine Learning on Proteomics Data., Front Genet. ,Epub ,2:103. PubMed

Reczko M, Maragkakis M, Alexiou P, Grosse I, Hatzigeorgiou AG. (2012) Functional microRNA targets in protein coding sequences., Bioinformatics. ,[Epub ahead of print] PubMed

Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G, Maragkakis M, Reczko M, Gerangelos S, Koziris N, Dalamagas T, Hatzigeorgiou AG. (2012) TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support., Nucleic Acids Res. ,40(Database issue) ,D222-9. PubMed

 
     
     
 
LAB MEMBERS

Lab Head
Hatzigeorgiou, Artemis (PhD)
Lab Members
Alexiou , Panagiotis (MSc)
Maragkakis , Manolis
Papadopoulos, Giorgos L.
Georgakilas, Georgios (MSc)
Paraskevopoulou, Maria
Vlachos, Ioannis
Lab Visitors
Reczko , Martin (PhD)
Riback, Joshua