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An HMM-based algorithm for evaluating rates of receptor-ligand binding kinetics from thermal fluctuation data

机译：一种基于HMM的热波动数据评价受体 - 配体结合动力学率的算法

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L. Ju; Y. D. Wang; Y. Hung; C.-F. J. Wu; C. Zhu;
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年度 2013
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1. An HMM-based algorithm for evaluating rates of receptor-ligand binding kinetics from thermal fluctuation data [J] . Ju Lining, Wang Yijie Dylan, Hung Ying, Bioinformatics . 2013,第12期

机译：基于HMM的算法，可根据热波动数据评估受体-配体结合动力学的速率
2. Intercellular Receptor-Ligand Binding and Thermal Fluctuations Facilitate Receptor Aggregation in Adhering Membranes [J] . Li Long, Hu Jinglei, Rozycki Bartosz, Nano letters . 2020,第1期

机译：细胞间受体 - 配体结合和热波动促进粘附膜中的受体聚集
3. Monitoring receptor-ligand interactions between surfaces by thermal fluctuations [J] . Chen W, Evans EA, McEver RP, Biophysical Journal . 2008,第2期

机译：通过热波动监测表面之间的受体-配体相互作用
4. Construction of Extracellular Matrix Mimics and Their Effect on the Kinetics and Thermodynamics of Receptor-Ligand Binding on Supported Lipid Bilayers(Abstract) [C] . Jessica M. Tucker, Todd M. Przybycien, Robert D. Tilton International Symposium on Runaway Reactions, Pressure Relief Design and Effluent Handling American Institute of Chemical Engineers/American Chemical Society Management Conference . 2005

机译：细胞外基质模拟的构建及其对受体 - 配体结合在负载脂质双层的动力学和热力学的影响（摘要）
5. Kinetic Nucleation Theory and Thermal Fluctuations in the Formation of Cosmic Dust. [D] . Fallest, David William. 2012

机译：动力学成核理论与宇宙尘埃形成中的热涨落。
6. An HMM-based algorithm for evaluating rates of receptor–ligand binding kinetics from thermal fluctuation data [O] . Lining Ju, Yijie Dylan Wang, Ying Hung, -1

机译：基于HMM的算法可根据热波动数据评估受体-配体结合动力学的速率
7. Figure 4: (A) One conserved sequence, which occurs 79 times in 46,264 binding site peaks from the ChIP-seq data-set. The mutation profile of this conserved sequence is illustrated, where ’_ ’ indicates this base is unchanged; DEL indicates this base is lost; INS X indicates a new base X is inserted in front of this base. (B) Several repeated elements patterns are listed. (C) In the first column, the top five DNA motifs, mined by meme-chip tools (Machanick Bailey, 2011) are illustrated. The resemblant conserved sequences, found by the CFSP algorithm are listed in the second column. In the third column, the position-specific scoring matrices, which are transformed from mutational information are listed. The similarity between meme motif and resemblant conserved sequence with PSSM format was calculated via a stamp motif comparison tool (Mahony Benos, 2007). The E-values for the similarity of those pairs is displayed in the fourth column. (D) One motif is selected in each group clustered by gkmsvm descriptors, and the corresponding motif found by the CFSP algorithm is listed below. (E) There are additional datasets (File No: ENCFF100GRL, ENCFF616IRT, ENCFF870CER, Target: SREBF1) collected from https://www.encodeproject.org. The top two motifs are selected in each file using meme tools, and the corresponding motifs found by our algorithm are listed below. [O] . -1

机译：图4：（a）一种保守序列，其发生在芯片-SEQ数据集中的46,264个结合位点峰值中的79倍。说明了这种保守序列的突变分布，其中'_'表示该碱度不变; del表示此基础丢失; INS X表示新的基础X插入此基础前面。（b）列出了几种重复的元素模式。（c）在第一栏中，示出了由MEME芯片工具（Machanick＆Bailey，2011）开采的前五个DNA主题。由CFSP算法发现的相应保守序列列于第二列中。在第三列中，列出了从突变信息转换的特定位置的评分矩阵。 MEME主题与PSSM格式的相似性与PSSM格式之间的相似性通过邮票图章比较工具（Mahony＆Benos，2007）计算。这些对相似性的电子值显示在第四列中。（d）在由GKMSVM描述符聚集的每个组中选择了一个图案，下面列出了CFSP算法的相应主题。（e）从https://www.encodeproject.org收集的，有附加数据集（文件no：cernff100grl，cenf616irl，conf8.20cer，target：srebf1）。使用MEME工具在每个文件中选择前两个图案，并且我们的算法发现的相应主题如下所示。

An HMM-based algorithm for evaluating rates of receptor-ligand binding kinetics from thermal fluctuation data

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