Showing 12 open source projects for "multiple sequence alignment"

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  • 1
    Protenix

    Protenix

    A trainable PyTorch reproduction of AlphaFold 3

    Protenix is an open-source, trainable PyTorch reimplementation of AlphaFold 3, developed by ByteDance with the goal of democratizing high-accuracy protein structure prediction for computational biology and drug-discovery research. Protenix provides a complete pipeline for turning protein sequences (with optional MSA / sequence alignment) or structural inputs (e.g. PDB/CIF) into full 3D atomic-level structure predictions. It supports both “full” models and lightweight variants such as “Protenix-Mini,” offering a trade-off between speed/compute cost and predictive accuracy — making structure prediction accessible even in resource-constrained environments. ...
    Downloads: 9 This Week
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  • 2
    Evo 2

    Evo 2

    Genome modeling and design across all domains of life

    ...The codebase is focused on local inference and generation through the Vortex inference stack rather than serving as a full training framework alone, although it also points users to training and fine-tuning resources. It supports multiple ways of working with the model, including forward passes, embeddings, generation workflows, notebooks, hosted APIs, and self-hosted deployment through NVIDIA NIM.
    Downloads: 2 This Week
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  • 3

    CPAT

    RNA coding potential assessment tool

    ...While still very useful, these approaches have several limitations: Most lncRNAs are less conserved and tend to be lineage specific which greatly limit the discrimination power of alignment-based methods. For example, of 550 lncRNAs detected from zebrafish, only 29 of them had detectable sequence
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    Downloads: 62 This Week
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  • 4
    TI2BioP allows mainly the calculation of topological indices (spectral moments) derived from inferred and artificial 2D structures of DNA, RNA and proteins being possible to carry out a structure-function correlation irrespective of sequence alignments. TI2BioP version 3.0 is a python platform with a graphical interface designed for Windows, Linux and Mac OS.
    Downloads: 0 This Week
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    UnsupervisedMT

    UnsupervisedMT

    Phrase-Based & Neural Unsupervised Machine Translation

    Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually refresh supervision signals. The project also provides scripts to fetch and preprocess monolingual data, learn BPE codes, and train cross-lingual embeddings that bootstrap unsupervised alignment between languages. ...
    Downloads: 7 This Week
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  • 6
    Maximum Common Genome Alignment (MCGA)

    Maximum Common Genome Alignment (MCGA)

    Pipeline for creating core genome alignments for phylogenetic analysis

    Maximum Common Genome Alignment (MCGA) Tool MCGA is a bioinformatics analysis tool written in Python for generating core genome alignment for bacterial whole genome sequences which can be used to construct phylogenetic trees.
    Downloads: 0 This Week
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  • 7
    ADOMA
    ADOMA stands for: Alternative Display Of Multiple Alignment. ADOMA can create four different displays of a multiple sequence alignment: a ClustalW alignment in HTML format, a simplified ClustalW alignment in HTML and/or txt format and a colored ClustalW alignment in HTML format. For examples of these outputfiles check the screenshots. ADOMA uses ClustalW to create the multiple alignment from DNA or protein sequences and displays them slightly different than the normal output of ClustalW. ...
    Downloads: 1 This Week
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  • 8
    FineSplice

    FineSplice

    Enhanced splice junction detection and estimation from RNA-Seq data

    Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. FineSplice requires Python 2.x (>= 2.6) with the following modules installed: pysam (http://code.google.com/p/pysam/) and scikit-learn (http://scikit-learn.org/). For further details check out our publication: Nucl.
    Downloads: 2 This Week
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  • 9

    Mix

    Mix is a tool to combine multiple assemblies from NGS data.

    Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the...
    Downloads: 0 This Week
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  • 10
    PepT-IDE is a protein analysis tool that is used for multiple sequence alignment, 3D visualization and displaying protein contact maps for protein sequences and structures. It also has feedback communication between the different views of the protein.
    Downloads: 0 This Week
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  • 11
    Biological Annotation Tool is a general-purpose high speed environment for manipulating biological sequence annotations in multiple input and output formats. A plugin-style API permits much extensibility.
    Downloads: 0 This Week
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  • 12
    trimAl can consider several parameters, alone or in multiple combinations, in order to select the most-reliable positions in the alignment. These include the proportion of sequences with a gap, the level of residue similarity and, if several alignments for the same set of sequences are provided, the consistency level of columns among alignments. Moreover, trimAl allows to manually select a set of columns and sequences to be removed from the alignment.
    Downloads: 0 This Week
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