Structure-seq is a high-throughput and quantitative method that provides genome-wide information on RNA structure at single-nucleotide resolution. Structure-seq can be performed both in vivo and in vitro to study RNA structure-function relationships, RNA regulation of gene expression and RNA ...
Structure-seq is a high-throughput and quantitative method that provides genome-wide information on RNA structure at single-nucleotide resolution. Structure-seq can be performed both in vivo and in vitro to study RNA structure-function relationships, RNA regulation of gene expression and RNA processing...
To figure out how Xist RNA is folded in mouse cells, we developed a new approach, Targeted Structure-Seq, to examine the conformation of large RNAs like Xist. Using computer modeling, we identified parts of Xist that are base paired into RNA duplexes. We also determined which parts of the...
Pipeline for investigating RNA structure-Seq data. Contribute to rnabioco/rnastruct development by creating an account on GitHub.
回答和翻译如下：Structure has no member named seq.没有成员的名字名为结构。
(2) Deep manifold learning methods do not have the ability to preserve the geometric structure of the high dimensional scRNA-seq data and correct batch effects in an end-to-end manner. Most methods require multiple separate steps, each with its own method, including batch correction (e.g., ...
To encode both the content and the structure of a table, we propose a novel structure-aware seq2seq architecture which consists of field-gating encoder and description generator with dual attention. In the encoding phase, we update the cell memory of the LSTM unit by a field gate and its ...
SHAPE-seq 是 DMS-seq 分析的新变体,其目标相同是识别 RNA 二级结构。 这些技术非常相似,除了不是甲基化 A和 C——被 DMS 甲基化的碱基—— SHAPE-seq 使用一种形状试剂,在这种情况下称为 1M7,它对 RNA 的 2' 羟基添加了更大的修饰。 这种方法是优越的,因为修改不仅限于 A和 C,而且可以击中 RNA 的...
SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment. SeqHound is based on the
SeqNMF is an algorithm which uses regularized convolutional non-negative matrix factorization to extract repeated sequential patterns from high-dimensional data. It has been validated using neural calcium imaging, spike data, and spectrograms, and allows the discovery of patterns directly from timeseries...