Search Results for "multiple sequence alignment" - Page 10

Showing 231 open source projects for "multiple sequence alignment"

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  • 1
    Sequence studio main package provides classes and interfaces for various kinds of sequence alignment. Differently from regular expressions it computes similarity with two initially unknown strings. Project page provides code generating applet.
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  • 2
    NeoBio is a Java class library of Computational Biology Algorithms. The current version consists mainly of pairwise sequence alignment algorithms such as the classical dynamic programming methods of Needleman-Wunsch and Smith-Waterman.
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  • 3
    This is a Java-based multiple protein sequence alignment editor. It will be used by protein scientists and annotators to analyse protein sequences, especially in the PIR file format. It will be connected to Clustalw (A multiple sequencea alignment algorit
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  • 4
    cut2 is a command line tool for extracting sections of each line from a file or stdin. cut2 is designed to treat multiple delimiters in sequence as a single delimiter.
    Downloads: 1 This Week
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  • 5
    fashion-clip

    fashion-clip

    CLIP model fine-tuned for zero-shot fashion product classification

    FashionCLIP is a domain-adapted CLIP model fine-tuned specifically for the fashion industry, enabling zero-shot classification and retrieval of fashion products. Developed by Patrick John Chia and collaborators, it builds on the CLIP ViT-B/32 architecture and was trained on over 800K image-text pairs from the Farfetch dataset. The model learns to align product images and descriptive text using contrastive learning, enabling it to perform well across various fashion-related tasks without...
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  • 6
    bge-base-en-v1.5

    bge-base-en-v1.5

    Efficient English embedding model for semantic search and retrieval

    ...This version (v1.5) improves retrieval performance and stabilizes similarity score distribution without requiring instruction-based prompts. With 768 embedding dimensions and a maximum sequence length of 512 tokens, it achieves strong performance across multiple MTEB benchmarks, nearly matching larger models while maintaining efficiency. It supports use via SentenceTransformers, Hugging Face Transformers, FlagEmbedding, and ONNX for various deployment scenarios. Typical usage includes normalizing output embeddings and calculating cosine similarity via dot product for ranking.
    Downloads: 0 This Week
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