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Aligns and merges sequence fragments resulting from shotgun sequencing or gene transcripts (expressed sequence tag (EST)) fragments in order to reconstruct the original segment or gene. EGassembler provides an automated as well as a user-customized analysis tool for cleaning, repeat masking, vector trimming, organelle masking, clustering and assembling of ESTs and genomic fragments. The web server is publicly available and provides the community an all-in-one online application web service. Running on a Sun Fire 15K supercomputer, a significantly large volume of data can be processed in a short period of time. The results can be used to functionally annotate genes, to facilitate splice alignment analysis, to link the transcripts to genetic and physical maps, design microarray chips, to perform transcriptome analysis and to map to KEGG metabolic pathways.


Preprocesses expressed sequence tag (EST) sequences. ESTprep identifies the location of features present in ESTs and allows the sequence to pass only if it meets various quality criteria. The objectives of ESTprep include identification of expected EST features and assurance that only high-quality sequences proceed to the later stages of the analysis. The EST features that are identified include restriction site, cloning vector, polyadenylation tail, library tag, and polyadenylation signal. ESTprep is highly configurable allowing simple incorporation into any high-throughput sequence processing environment.

ESTAP / EST Analysis Pipeline

Proposes a set of analytical procedures that automatically verify, cleanse, store and analyze ESTs (Expressed Sequence Tags) generated on high-throughput platforms. ESTAP uses a relational database to store sequence data and analysis results, which facilitates both the search for specific information and statistical analysis. ESTAP provides for easy viewing of the original and cleansed data, as well as the analysis results via a Web browser. It also allows the data owner to submit selected sequences to dbEST in a semi-automated fashion.


Extends the volume of data that can be mapped in reasonable time, and makes this improved efficiency available as a web service. e2g is a web-based server which efficiently maps large expressed sequence tag (EST) and cDNA datasets to genomic DNA. It uses an efficient index structure precomputed for the EST collection under consideration. The index structure allows the user to find highly conserved matches between the genomic sequence and the EST collection much more quickly than with a scanning-based method.


Provides a public sequence processing service for raw expressed sequence tag (EST) traces. WebTraceMiner focuses on detection and mining of sequence features that help characterize 3′ and 5′ termini of cDNA inserts, including vector fragments, adapter/linker sequences, insert-flanking restriction endonuclease recognition sites and polyA or polyT tails. WebTraceMiner complements other public EST resources and facilitates data validation and mining of error-prone ESTs (e.g. discovery of new functional motifs).


Supports the search of functional annotations of novel transcript sequences through automatic analysis of EST sequences. ESTAnnotator, in a first quality check step repeats, masks vector parts and low quality sequences. Then successive steps of BLAST searching against suitable databases and EST clustering are performed. Already known transcripts present within mRNA and genomic DNA reference databases are identified. Subsequently, tools for the clustering of anonymous ESTs and for further database searches at the protein level are executed. ESTAnnotator was successfully applied for the systematic identification and characterisation of novel human genes involved in cartilage/bone formation, growth, differentiation and homeostasis.


Analyses and transforms large collections of raw DNA-sequence data by calling the quality of bases, screening and removing vector sequences, assembling and rewriting consensus sequences of redundant input files into a unigene expressed sequence tag (EST) data set and finally through translation, amino acid sequence similarity searches, annotation of public databases and functional data. PipeOnline generates an annotated database, retaining the processed unigene sequence, clone/file history, alignments with similar sequences, and proposed functional classification, if available. Functional annotation is automatic and based on a novel method that relies on homology of amino acid sequence multiplicity within GenBank records. PipeOnline offers customization for individual projects (MyPipeOnline), automated updating and alert service.


Enables the user to easily upload, organize, visualize and search the different types of data generated in an expressed sequence tag (EST) project pipeline. JUICE is a data management system which allows a branched pipeline to be established, modified and expanded, during the course of an EST project. The web interfaces and tools in JUICE enable the users to visualize the information in a graphical, user-friendly manner. The user may browse or search for sequences and/or sequence information within all the branches of the pipeline. The user can search using terms associated with the sequence name, annotation or other characteristics stored in JUICE and associated with sequences or sequence groups. Groups of sequences can be created by the user, stored in a clipboard and/or downloaded for further analyses. Different user profiles restrict the access of each user depending upon their role in the project.


Processes and annotates sequence data from expressed sequence tag (EST) projects. ESTpass executes a back-end EST analysis pipeline consisting of three consecutive steps. The first is cleansing the input EST sequences. The second is clustering and assembling the cleansed EST sequences using d2_cluster and CAP3 programs and producing putative transcripts. From the CAP3 output, ESTpass detects chimeric EST sequences which are confirmed through comparison with a database. The last step is annotating the putative transcript sequences using RefSeq, InterPro, GO and KEGG gene databases according to user-specified options. The major advantages of ESTpass are the integration of cleansing and annotating processes, rigorous chimeric EST detection, exhaustive annotation, and email reporting to inform the user about the progress and to send the analysis results. The ESTpass results include three reports (summary, cleansing and annotation) and download function, as well as graphic statistics. They can be retrieved and downloaded using a standard web browser.


Provides a comprehensive workflow system for expressed sequence tag (EST) data management and analysis. ESTExplorer uses a distributed control approach in which the most appropriate bioinformatics tools are implemented over different dedicated processors. Species-specific repeat masking and conceptual translation are in-built. ESTExplorer accepts a set of ESTs in FASTA format which can be analysed using programs selected by the user. After pre-processing and assembly, the dataset is annotated at the nucleotide and protein levels, following conceptual translation. Users may optionally provide ESTExplorer with assembled contigs for annotation purposes. Functionally annotated contigs/ESTs can be analysed individually. The overall outputs are gene ontologies, protein functional identifications in terms of mapping to protein domains and metabolic pathways.


Provides a web-based expressed sequence tag (EST) analysis pipeline for gene assignment and systematic functional annotation of large amounts of DNA sequences. OREST allows mapping of user data to the fungal model organism Saccharomyces cerevisiae as well as to several mammalian datasets. Automated functional assignment of the gene products can be performed via FunCat or Gene Ontology (GO) annotation schemes. Mapping to the human dataset predicts also the association of the ESTs with diseases. Over- und under-represented features from functional annotation and disease relevance are obtained through a statistical analysis. Advantage and usability of the OREST EST analysis pipeline has been shown in a successful analysis of more than 3000 ESTs of the common marmoset monkey (Callithrix jacchus) within an international scientific consortium.


Provides a bioinformatics solution for expressed sequence tags (EST) data entry, database management, GenBank submission, process control and data retrieval from a unified web interface. EST-PAGE can be easily customized and adapted by groups working on diverse EST sequencing projects. Besides providing a tool for handling EST submission to GenBank, the interface handles many aspects of EST project information from tracking cDNA clone and library information, to extended analyses of sequence redundancy. Specifically, clone storage, handling and growth information can be stored and retrieved for each library.


Is designed for uniform data processing and storage for large-scale Expressed Sequence Tag (EST) sequencing projects. ESTweb package provides for: (a) reception of sequencing chromatograms; (b) sequence processing such as base-calling, vector screening, comparison with public databases; (c) storage of data and analysis in a relational database, (d) generation of a graphical report of individual sequence quality; and (e) issuing of reports with statistics of productivity and redundancy. The software facilitates real-time monitoring and evaluation of EST sequence acquisition progress along an EST sequencing project.

ESTPiper / Expressed Sequence Tag Piper

Streamlines the typical process of Expressed Sequence Tag (EST) analysis. ESTPiper web interface guides users through each step of base calling, data cleaning, assembly, genome alignment, annotation, analysis of gene ontology (GO), and microarray oligonucleotide probe design. Each step is modularized. Therefore, a user can execute them separately or together in batch mode. In addition, the user has control over the parameters used by the underlying programs. The user can also download intermediate results and port files to separate programs for further analysis. In addition, the server provides a time-stamped description of the run history for reproducibility. The pipeline can also be installed locally, allowing researchers to modify ESTPiper to suit their own needs.

MediPlEx / MEDIcago truncatula multiPLe EXpression analysis

Identifies genes activated in Medicago truncatula AM roots. MediPlEx combines the different kinds of gene expression datasets. It gathers information on the composition of the relevant Tentative Consensus sequences (TCs) from SAMS and calculates logarithmic likelihood ratios, an in-silico expression measure, for the selected TCs. This tool allows users to analyze and cluster transcriptomics data, visualize gene expression in 3D and find cluster of genes with correlating expression.


Provides a workflow for large-scale analysis of transcriptomic data with the most appropriate bioinformatics tools for data management and analysis. TransSeqAnnotator automatically cleans, clusters, assembles and generates consensus sequences, conceptually translates these into possible protein products and assigns putative function based on various DNA and protein similarity searches. Excretory/secretory (ES) proteins inferred from expressed sequence tags (ESTs)/short reads are also identified. The TranSeqAnnotator accepts FASTA format raw and quality ESTs along with protein and short read sequences and are analysed with user selected programs. After pre-processing and assembly, the dataset is annotated at the nucleotide, protein and ES protein levels.

ESTIMA / Expressed Sequence Tag Information Management and Annotation

Meets the Expressed Sequence Tags (EST) annotation and data management requirements of multiple high-throughput EST sequencing projects. ESTIMA is anchored on individual ESTs and organized around different properties of ESTs including chromatograms, base-calling quality scores, structure of assembled transcripts, and multiple sources of comparison to infer functional annotation, Gene Ontology (GO) associations, and cDNA library information. ESTIMA consists of a relational database schema and a set of interactive query interfaces. These are integrated with a suite of web-based tools that allow the user to query and retrieve information. Further, query results are interconnected among the various EST properties. Users may run their own EST processing pipeline, search against preferred reference genomes, and use any clustering and assembly algorithm. The ESTIMA database schema is very flexible and accepts output from any EST processing and assembly pipeline.

ParPEST / Parallel Processing of ESTs

Performs an exhaustive and reliable analysis on expressed sequence tags (EST) data. ParPEST also provides a curated set of information based on a relational database. Moreover, it is designed to reduce execution time of the specific steps required for a complete analysis using distributed processes and parallelized software. It is conceived to run on low requiring hardware components, to fulfill increasing demand, typical of the data used, and scalability at affordable costs.