ALGGEN

ALGGEN provides a collection of computational tools for sequence analysis, including multiple sequence alignment, clustering, assembly of expressed sequence tags (ESTs), transcription factor binding site (TFBS) prediction, repeat and motif identification, and visualization to support genomics, transcriptomics, comparative genomics, and structural biology.

Key Features:

• Multiple Sequence Alignments and Clustering: Performs multiple sequence alignments and clustering for comparative genomics and evolutionary analysis.
• EST Assembly: Supports assembly of expressed sequence tags (ESTs) for gene discovery and transcriptome analysis.
• TFBS Prediction (PROMO version 2.0): Includes PROMO version 2.0 for predicting transcription factor binding sites in single sequences or groups of related sequences.
• Positional Weight Matrix Construction: Constructs positional weight matrices from known TFBS to enable species- or taxon-specific searches in DNA sequences.
• MREPATT (Pattern and Repeat Identification): Identifies exact consecutive repeats of short sequences and assesses statistical significance by comparison to random sequences generated via a Markovian model.
• MALGEN (Sequence Correspondence Visualization): Visualizes sequence correspondences among long DNA sequences.
• ABS Database Integration: Incorporates the ABS database of transcription factor binding sites in promoters of orthologous vertebrate genes and supports generation of artificial datasets and evaluation of motif-finding programs.
• Diffraction Pattern Visualization: Provides visualization of diffraction patterns from partially ordered fibres with helical symmetry for analysis of DNA and protein coiled coils.

Scientific Applications:

• Genomics and Transcriptomics: Supports gene discovery, transcriptome analysis, and studies of gene regulation via TFBS prediction and EST assembly.
• Comparative Genomics: Enables evolutionary and comparative analyses through multiple sequence alignments, clustering, and MALGEN visualizations.
• Structural Biology: Supports analysis of macromolecular structures with helical symmetry by visualizing diffraction patterns from partially ordered fibres and coiled coils.

Methodology:

Computational methods explicitly include multiple sequence alignment and clustering algorithms, EST assembly algorithms, TFBS prediction via PROMO v2.0 and construction of positional weight matrices, repeat detection with MREPATT and statistical significance assessment against random sequences generated by a Markovian model, MALGEN visualization of sequence correspondences, and use of the ABS database for curated TFBS datasets, artificial dataset generation, and motif-finder evaluation.