语法糖:为聚糖结构设计正则表达式框架。

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2024-04-19 eCollection Date: 2024-01-01 DOI:10.1093/bioadv/vbae059
Alexander R Bennett, Daniel Bojar
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引用次数: 0

摘要

动机:由于聚糖序列复杂,对其进行结构分析是糖生物学领域的重大挑战。诸如分析 N-聚糖中 α1-6 分支的序列内容等研究问题具有生物学意义,但却很难实现自动化:在这里,我们介绍了一种正则表达式系统,该系统专为聚糖设计,特征完整,并与正则表达式格式紧密结合。我们用它来注释任意复杂程度的聚糖图案,对指定的序列片段进行差异表达分析,或以自动化方式阐明凝集素的分支特异性结合。我们相信,聚糖正则表达式将增强这些序列的计算分析能力:我们的聚糖正则表达式框架是用 Python 实现的,并纳入了开源的 glycowork 软件包(版本 1.1+)。代码和文档可从 https://github.com/BojarLab/glycowork/blob/master/glycowork/motif/regex.py 获取。
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Syntactic sugars: crafting a regular expression framework for glycan structures.

Motivation: Structural analysis of glycans poses significant challenges in glycobiology due to their complex sequences. Research questions such as analyzing the sequence content of the α1-6 branch in N-glycans, are biologically meaningful yet can be hard to automate.

Results: Here, we introduce a regular expression system, designed for glycans, feature-complete, and closely aligned with regular expression formatting. We use this to annotate glycan motifs of arbitrary complexity, perform differential expression analysis on designated sequence stretches, or elucidate branch-specific binding specificities of lectins in an automated manner. We are confident that glycan regular expressions will empower computational analyses of these sequences.

Availability and implementation: Our regular expression framework for glycans is implemented in Python and is incorporated into the open-source glycowork package (version 1.1+). Code and documentation are available at https://github.com/BojarLab/glycowork/blob/master/glycowork/motif/regex.py.

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