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  • GitHub - usadellab Helixer: Using Deep Learning to predict gene . . .
    Helixer is a tool for structural genome annotation It utilizes Deep Neural Networks and a Hidden Markov Model to directly provide primary gene models in a gff3 file
  • Helixer: ab initio prediction of primary eukaryotic gene models . . .
    Here we present Helixer, an artificial intelligence-based tool for ab initio gene prediction that delivers highly accurate gene models across fungal, plant, vertebrate and invertebrate genomes
  • Helixer structural gene annotation - plabipd
    Helixer is being actively maintained and improved please do not submit the same genome to be processed mutliple times The results will be unchanged and will use resouces unnecessarily we currently support compressed ( gz zip bz2) and uncompressed input files
  • Helixer: cross-species gene annotation of large eukaryotic genomes . . .
    We present Helixer, a framework for the development and usage of a cross-species deep learning model that improves significantly on performance and generalizability when compared to more traditional methods
  • AI tool “Helixer” identifies genes in newly sequenced organisms
    Helixer is the first AI tool that can reliably identify genes in such diverse groups of organisms – from plants and fungi to insects and vertebrates Every year, thousands of genomes are sequenced worldwide, many of them from species that have barely been studied
  • Helixer: ab initio prediction of primary eukaryotic gene models
    Their tool, called Helixer, uses artificial intelligence to predict genes directly from raw DNA sequences This is known as ab initio prediction, meaning the tool makes decisions based solely on the sequence itself rather than relying on extra datasets or lab experiments
  • Helixer–de novo Prediction of Primary Eukaryotic Gene . . . - bioRxiv
    Helixer’s predictions can be used as is or could be integrated in pipelines to boost quality further Moreover, there is substantial potential for further improvements and advancements in gene calling with Deep Learning
  • Helixer终极实战指南：深度学习基因注释的完整进阶攻略-CSDN博客
    还在为复杂的基因组注释工作而头疼吗？ Helixer作为一款基于深度学习的基因预测工具，正通过AI技术重新定义生物信息学分析流程。 本文将带你从零开始，掌握这款强大工具的核心用法与实战技巧，让你的基因注释工作事半功倍。
  • Nat. Methods | Helixer: 深度学习驱动的真核基因预测
    研究人员开发了 Helixer，这是一种结合深度学习与 隐马尔可夫模型 （HMM）的混合框架，可在没有 转录组数据 的情况下直接进行高质量的基因模型预测。 Helixer 首先利用深度神经网络从核苷酸序列中学习局部与全局序列特征，再通过 HMM 进行结构化预测，使输出基因模型符合真实生物学结构。 该方法在多个模式生物上显著提升外显子边界、编码序列、转录本结构等的预测质量。 研究人员还构建了 Helixer 的可扩展软件包和可视化工具，为快速、自动化的基因组注释提供了新的解决方案。 随着基因组测序技术的快速普及，越来越多的真核基因组被生成，但基因结构注释仍然是瓶颈步骤。 真核基因的结构比原核基因复杂得多，包含： 弱化、模糊或分散的信号序列。
  • HELIXER | ELIXIR
    HELIXER Enables you to set up and train models for ab initio prediction of gene structure That is, to perform "gene calling" and identify which base pairs in a genome belong to the UTR CDS Intron of genes





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