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- Volume 20, Issue 7, 2017
Combinatorial Chemistry & High Throughput Screening - Volume 20, Issue 7, 2017
Volume 20, Issue 7, 2017
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Recognizing and Predicting Thioether Bridges Formed by Lanthionine and β-Methyllanthionine in Lantibiotics Using a Random Forest Approach with Feature Selection
Authors: ShaoPeng Wang, Yu-Hang Zhang, Ning Zhang, Lei Chen, Tao Huang and Yu-Dong CaiBackground: Lantibiotics, which are usually produced from Gram-positive bacteria, are regarded as one type of special bacteriocins. Lantibiotics have unsaturated amino acid residues formed by lanthionine (Lan) and β-methyllanthionine (MeLan) residues as a ring structure in the peptide. They are derived from the serine and threonine residues and are essential to preventing the growth of other similar strains. Method: In t Read More
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Prediction and Identification of Krüppel-Like Transcription Factors by Machine Learning Method
Authors: Zhijun Liao, Xinrui Wang, Xingyong Chen and Quan ZouAim and Objective: The Krüppel-like factors (KLFs) are a family of containing Zn finger(ZF) motif transcription factors with 18 members in human genome, among them, KLF18 is predicted by bioinformatics. KLFs possess various physiological function involving in a number of cancers and other diseases. Here we perform a binary-class classification of KLFs and non-KLFs by machine learning methods. Material and Method: The p Read More
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Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network
Authors: Chenglin Liu, Peng Cui and Tao HuangBackground: The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big problems in cell cycle-regulated gene detection. Methods: Here, a computational framework called DLGene was proposed for cell cycle-regulated gene detection. It is based o Read More
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A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class
More LessAim and Objective: Correct prediction of protein structural class is beneficial to investigation on protein functions, regulations and interactions. In recent years, several computational methods have been proposed in this regard. However, based on various features, it is still a great challenge to select proper classification algorithm and extract essential features to participate in classification. Material and Methods: In this study, a Read More
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Prediction of Lysine Malonylation Sites Based on Pseudo Amino Acid
Authors: Qilin Xiang, Kaiyan Feng, Bo Liao, Yuewu Liu and Guohua HuangAim and Objective: Protein malonylation is a newly discovered post-translational modification. Malonylation is known to closely be associated with type 2 diabetes and to play its regulatory role in fatty acid oxidation and the associated genetic disease. Identifying protein malonylations might lay a solid foundation to explore malonylation function. Due to the limitations of experimental techniques, it is a great challenge to fast and Read More
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Computational Prediction of Protein Epsilon Lysine Acetylation Sites Based on a Feature Selection Method
Authors: JianZhao Gao, Xue-Wen Tao, Jia Zhao, Yuan-Ming Feng, Yu-Dong Cai and Ning ZhangAim and Objective: Lysine acetylation, as one type of post-translational modifications (PTM), plays key roles in cellular regulations and can be involved in a variety of human diseases. However, it is often high-cost and time-consuming to use traditional experimental approaches to identify the lysine acetylation sites. Therefore, effective computational methods should be developed to predict the acetylation sites. In this stud Read More
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Prediction of the Ebola Virus Infection Related Human Genes Using Protein-Protein Interaction Network
Authors: HuanHuan Cao, YuHang Zhang, Jia Zhao, Liucun Zhu, Yi Wang, JiaRui Li, Yuan-Ming Feng and Ning ZhangBackground: Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous. Objective: According to the “guilt by association” (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried Read More
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The Safety of Ovarian Preservation in Stage I Endometrial Endometrioid Adenocarcinoma Based on Propensity Score Matching
More LessBackground: Most patients with early stage endometrial endometrioid adenocarcinoma (EEAC) are treated with hysterectomy and bilateral oophorectomy. But this surgical menopause leads to long-term sequelae for premenopausal women, especially for young women of childbearing age. This population-based study was to evaluate the safety of ovarian preservation in young women with stage I EEAC. Methods: Patien Read More
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Volumes & issues
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Volume 28 (2025)
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Volume 27 (2024)
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Volume 26 (2023)
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Volume 25 (2022)
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Volume 24 (2021)
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Volume 23 (2020)
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Volume 22 (2019)
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Volume 21 (2018)
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Volume 20 (2017)
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Volume 19 (2016)
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Volume 18 (2015)
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Volume 17 (2014)
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Volume 16 (2013)
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Volume 15 (2012)
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Volume 14 (2011)
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Volume 13 (2010)
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Volume 12 (2009)
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Volume 11 (2008)
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Volume 10 (2007)
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Volume 9 (2006)
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Volume 8 (2005)
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Volume 7 (2004)
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Volume 6 (2003)
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Volume 5 (2002)
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Volume 4 (2001)
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Volume 3 (2000)
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Label-Free Detection of Biomolecular Interactions Using BioLayer Interferometry for Kinetic Characterization
Authors: Joy Concepcion, Krista Witte, Charles Wartchow, Sae Choo, Danfeng Yao, Henrik Persson, Jing Wei, Pu Li, Bettina Heidecker, Weilei Ma, Ram Varma, Lian-She Zhao, Donald Perillat, Greg Carricato, Michael Recknor, Kevin Du, Huddee Ho, Tim Ellis, Juan Gamez, Michael Howes, Janette Phi-Wilson, Scott Lockard, Robert Zuk and Hong Tan
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