Search Results for "multiple sequence alignment" - Page 2
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Showing 40 open source projects for "multiple sequence alignment"
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XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
...Pretrained checkpoints cover dozens of languages and multiple model sizes, balancing quality and compute needs. -
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BasicSR
Winning Solution in NTIRE19 Challenges on Video Restoration
BasicSR is a deep learning framework designed for advanced video restoration tasks such as video super-resolution, deblurring, and denoising. Unlike single-image restoration models, EDVR addresses the temporal dimension by aligning multiple video frames using deformable convolutional layers in a coarse-to-fine manner, allowing it to effectively handle large motion and complex scene dynamics. The architecture includes bespoke modules (e.g., Pyramid, Cascading and Deformable alignment and Temporal Spatial Attention fusion) that align information across frames and emphasize important features for restoration, enabling state-of-the-art performance on benchmarks such as the REDS challenge. ... -
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TFKit
Handling multiple nlp task in one pipeline
TFKit is a tool kit mainly for language generation. It leverages the use of transformers on many tasks with different models in this all-in-one framework. All you need is a little change of config. You can use tfkit for model training and evaluation with tfkit-train and tfkit-eval. The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the... -
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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.
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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. ... -
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Tacotron-2
DeepMind's Tacotron-2 Tensorflow implementation
...The repository is structured as a full training pipeline: dataset preparation, preprocessing into spectrograms, Tacotron training, WaveNet (or Griffin-Lim) vocoder training, and final waveform synthesis. It includes directory layouts and logging directories for multiple datasets such as LJSpeech and M-AILABS en_US/en_UK, making it easier to adapt to new English corpora. Separate log trees track mel-spectrograms, attention plots, evaluation audio, and vocoder outputs, so you can inspect how alignment and audio quality evolve over time. -
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Matplotlib tutorial
Matplotlib tutorial for beginner
...As the tutorial builds progressively, learners can gradually advance from simple static plots to more complex visualizations, learning how to control figure size, add multiple subplots, adjust plot aesthetics, and handle different data types. Because it is code-first, users can copy, modify, and run the examples on their own datasets, encouraging experimentation and deepening understanding. -
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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. -
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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. ...
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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. -
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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... -
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Torchlit
Torchlight 2 aid tool. scroll skills,middle click multiple skills
This tool helps players use the mouse scroll and middle click to scroll through spells/skills and activate a sequence of quickslot skills respectively. -
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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.
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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.
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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.
