摘要翻译：
多序列比对是当今生物学中的一个关键过程，寻找多个序列的相关比对比优化一些不可能的评价函数更具挑战性。我们处理多序列比对的方法集中在一个新的图模型：因子图模型中的结构构建上。这个模型依赖于对原始问题的基于块的表述，这种表述似乎是捕捉对齐的进化方面的最合适的方法之一。这些结构是由一群蚂蚁根据属于不同序列的块之间的关系，在因子图中放置信息素而隐含地建立的。
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英文标题：
《An Ant-Based Model for Multiple Sequence Alignment》
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作者：
Fr\'ed\'eric Guinand (LITIS), Yoann Pign\'e (LITIS)
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最新提交年份：
2008
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Quantitative Methods        定量方法
分类描述：All experimental, numerical, statistical and mathematical contributions of value to biology
对生物学价值的所有实验、数值、统计和数学贡献
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  Multiple sequence alignment is a key process in today's biology, and finding a relevant alignment of several sequences is much more challenging than just optimizing some improbable evaluation functions. Our approach for addressing multiple sequence alignment focuses on the building of structures in a new graph model: the factor graph model. This model relies on block-based formulation of the original problem, formulation that seems to be one of the most suitable ways for capturing evolutionary aspects of alignment. The structures are implicitly built by a colony of ants laying down pheromones in the factor graphs, according to relations between blocks belonging to the different sequences.
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PDF链接：
https://arxiv.org/pdf/0803.2092