bluuebunny/crossref_metadata_2025_split huggingface dataset:
The C-Terminal Portion of the Nucleocapsid Protein Demonstrates SARS-CoV Antigenicity
Authors: Liu Guozhen , Hu Shaohui , Hu Yongwu , Chen Peng , Yin Jianning , Wen Jie , Wang Jingqiang , Lin Liang , Liu Jinxiu , You Bo , Yin Ye , Li Shuting , Wang Hao , Ren Yan , Ji Jia , Zhao Xiaoqian , Sun Yongqiao , Zhang Xiaowei , Fang Jianqiu , Wang Jian , Liu Siqi , Yu Jun , Zhu Heng , Yang Huanming 
Published: November 2016

Abstract
In order to develop clinical diagnostic tools for rapid detection of SARS-CoV (severe acute respiratory syndrome-associated coronavirus) and to identify candidate proteins for vaccine development, the C-terminal portion of the nucleocapsid (NC) gene was amplified using RT-PCR from the SARS-CoV genome, cloned into a yeast expression vector (pEGH), and expressed as a glutathione S-transferase (GST) and Hisx6 double-tagged fusion protein under the control of an inducible promoter. Western analysis on the purified protein confirmed the expression and purification of the NC fusion proteins from yeast. To determine its antigenicity, the fusion protein was challenged with serum samples from SARS patients and normal controls. The NC fusion protein demonstrated high antigenicity with high specificity, and therefore, it should have great potential in designing clinical diagnostic tools and provide useful information for vaccine development.
A Strategy for Searching Antigenic Regions in the SARS-CoV Spike Protein
Authors: Ren Yan , Zhou Zhengfeng , Liu Jinxiu , Lin Liang , Li Shuting , Wang Hao , Xia Ji , Zhao Zhe , Wen Jie , Zhou Cuiqi , Wang Jingqiang , Yin Jianning , Xu Ningzhi , Liu Siqi 
Published: November 2016

Abstract
In the face of the worldwide threat of severe acute respiratory syndrome (SARS) to human life, some of the most urgent challenges are to develop fast and accurate analytical methods for early diagnosis of this disease as well as to create a safe anti-viral vaccine for prevention. To these ends, we investigated the antigenicity of the spike protein (S protein), a major structural protein in the SARS-coronavirus (SARS-CoV). Based upon the theoretical analysis for hydrophobicity of the S protein, 18 peptides were synthesized. Using Enzyme-Linked Immunosorbent Assay (ELISA), these peptides were screened in the sera from SARS patients. According to these results, two fragments of the S gene were amplified by PCR and cloned into pET-32a. Both S fragments were expressed in the BL-21 strain and further purified with an affinity chromatography. These recombinant S fragments were confirmed to have positive cross-reactions with SARS sera, either by Western blot or by ELISA. Our results demonstrated that the potential epitope regions were located at Codons 469–882 in the S protein, and one epitope site was located at Codons 599–620. Identification of antigenic regions in the SARS-CoV S protein may be important for the functional studies of this virus or the development of clinical diagnosis.
EST Pipeline System: Detailed and Automated EST Data Processing and Mining
Authors: Xu Hao , He Ling , Zhu Yuanzhong , Huang Wei , Fang Lijun , Tao Lin , Zhu Yuedong , Cai Lin , Xu Huayong , Zhang Liang , Yu Hong , Zhou Yan 
Published: November 2016

Abstract
Expressed sequence tags (ESTs) are widely used in gene survey research these years. The EST Pipeline System, software developed by Hangzhou Genomics Institute (HGI), can automatically analyze different scalar EST sequences by suitable methods. All the analysis reports, including those of vector masking, sequence assembly, gene annotation, Gene Ontology classification, and some other analyses, can be browsed and searched as well as downloaded in the Excel format from the web interface, saving research efforts from routine data processing for biological rules embedded in the data.
Genetic Algorithms Applied to Multi-Class Clustering for Gene Expression Data
Authors: Pan Haiyan , Zhu Jun , Han Danfu 
Published: November 2016

Abstract
A hybrid GA (genetic algorithm)-based clustering (HGACLUS) schema, combining merits of the Simulated Annealing, was described for finding an optimal or near-optimal set of medoids. This schema maximized the clustering success by achieving internal cluster cohesion and external cluster isolation. The performance of HGACLUS and other methods was compared by using simulated data and open microarray gene-expression datasets. HGACLUS was generally found to be more accurate and robust than other methods discussed in this paper by the exact validation strategy and the explicit cluster number.
Bioinformatics-Based Identification of Chemosensory Proteins in African Malaria Mosquito, Anopheles Gambiae
Authors: Li Zhengxi , Shen Zuorui , Zhou Jingjiang , Field Lin 
Published: November 2016

Abstract
Chemosensory proteins (CSPs) are identifiable by four spatially conserved Cysteine residues in their primary structure or by two disulfide bridges in their tertiary structure according to the previously identified olfactory specific-D related proteins. A genomics- and bioinformatics-based approach is taken in the present study to identify the putative CSPs in the malaria-carrying mosquito, Anopheles gambiae. The results show that five out of the nine annotated candidates are the most possible Anopheles CSPs of A. gambiae. This study lays the foundation for further functional identification of Anopheles CSPs, though all of these candidates need additional experimental verification.
Dexamethasone-Inducible Green Fluorescent Protein Gene Expression in Transgenic Plant Cells
Authors: Tang Wei , Collver Hilary , Kinken Katherine 
Published: November 2016

Abstract
Genomic research has made a large number of sequences of novel genes or expressed sequence tags available. To investigate functions of these genes, a system for conditional control of gene expression would be a useful tool. Inducible transgene expression that uses green fluorescent protein gene (gfp) as a reporter gene has been investigated in transgenic cell lines of cotton (COT; Gossypium hirsutum L.), Fraser fir [FRA; Abies fraseri (Pursh) Poir], Nordmann fir (NOR; Abies nordmanniana Lk.), and rice (RIC; Oryza sativa L. cv. Radon). Transgenic cell lines were used to test the function of the chemical inducer dexamethasone. Inducible transgene expression was observed with fluorescence and confocal microscopy, and was confirmed by northern blot analyses. Dexamethasone at 5 mg/L induced gfp expression to the nearly highest level 48 h after treatment in COT, FRA, NOR, and RIC. Dexamethasone at 10 mg/L inhibited the growth of transgenic cells in FRA and NOR, but not COT and RIC. These results demonstrated that concentrations of inducer for optimum inducible gene expression system varied among transgenic cell lines. The inducible gene expression system described here was very effective and could be valuable in evaluating the function of novel gene.
Preliminary Study on Detecting the SARS-CoV Specific Target cDNA Fragments by Multiplex PCR
Authors: Chen Wenbing , Li Shousong , Shao Biying , Zheng Teng , Jiang Shuxun , Huang Xiaorong , Cai Kaizhen , Zhang Zhideng 
Published: November 2016

Abstract
The multiplex polymerase chain reaction (PCR) technique was applied to detect the SARS-CoV (severe acute respiratory syndrome-associated coronavirus) specific target cDNA fragments in the present study. The target cDNA fragments of SARS-CoV were synthesized artificially according to the genome sequence of SARS-CoV in GenBank submitted by The Chinese University of Hong Kong, and were used as simulated positive samples. Five primers recommended by World Health Organization (WHO) were used to amplify the fragments by single PCR and multiplex PCR. Three target cDNA fragments (121, 182 and 302 bp), as well as the three different combinations of any two of these fragments, were amplified by single PCR. The combination of these three fragments was amplified by multiplex PCR. The results indicated that the multiplex PCR technique could be applied to detect the SARS-CoV specific target cDNA fragments successfully.
Emerging Genomic and Proteomic Evidence on Relationships Among the Animal, Plant and Fungal Kingdoms
Authors: Stiller John W. 
Published: November 2016

Abstract
Sequence-based molecular phylogenies have provided new models of early eukaryotic evolution. This includes the widely accepted hypothesis that animals are related most closely to fungi, and that the two should be grouped together as the Opisthokonta. Although most published phylogenies have supported an opisthokont relationship, a number of genes contain a tree-building signal that clusters animal and green plant sequences, to the exclusion of fungi. The alternative tree-building signal is especially intriguing in light of emerging data from genomic and proteomic studies that indicate striking and potentially synapomorphic similarities between plants and animals. This paper reviews these new lines of evidence, which have yet to be incorporated into models of broad scale eukaryotic evolution.
Microarray and Proteomic Analysis of Brassinosteroid- and Gibberellin-Regulated Gene and Protein Expression in Rice
Authors: Yang Guangxiao , Komatsu Setsuko 
Published: November 2016

Abstract
Brassinosteroid (BR) and gibberellin (GA) are two groups of plant growth regulators essential for normal plant growth and development. To gain insight into the molecular mechanism by which BR and GA regulate the growth and development of plants, especially the monocot plant rice, it is necessary to identify and analyze more genes and proteins that are regulated by them. With the availability of draft sequences of two major types, japonica and indica rice, it has become possible to analyze expression changes of genes and proteins at genome scale. In this review, we summarize rice functional genomic research by using microarray and proteomic approaches and our recent research results focusing on the comparison of cDNA microarray and proteomic analyses of BR- and GA-regulated gene and protein expression in rice. We believe our findings have important implications for understanding the mechanism by which BR and GA regulate the growth and development of rice.
Post-Transcriptional Gene Silencing Induced by Short Interfering RNAs in Cultured Transgenic Plant Cells
Authors: Tang Wei , Samuels Vanessa , Whitley Nicki , Bloom Nicole , DeLaGarza Tinya , Newton Ronald J. 
Published: November 2016

Abstract
Short interfering RNA (siRNA) is widely used for studying post-transcriptional gene silencing and holds great promise as a tool for both identifying function of novel genes and validating drug targets. Two siRNA fragments (siRNA-a and -b), which were designed against different specific areas of coding region of the same target green fluorescent protein (GFP) gene, were used to silence GFP expression in cultured gfp transgenic cells of rice (Oryza sativa L.; OS), cotton (Gossypium hirsutum L.; GH), Fraser fir [Abies fraseri (Pursh) Poir; AF], and Virginia pine (Pinus virginiana Mill.; PV). Differential gene silencing was observed in the bombarded transgenic cells between two siRNAs, and these results were consistent with the inactivation of GFP confirmed by laser scanning microscopy, Northern blot, and siRNA analysis in tested transgenic cell cultures. These data suggest that siRNA-mediated gene inactivation can be the siRNA specific in different plant species. These results indicate that siRNA is a highly specific tool for targeted gene knockdown and for establishing siRNA-mediated gene silencing, which could be a reliable approach for large-scale screening of gene function and drug target validation.
The Path to Enlightenment: Making Sense of Genomic and Proteomic Information
Authors: Maurer Martin H. 
Published: November 2016

Abstract
Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.
Application of Proteomics in the Study of Tumor Metastasis
Authors: Cai Zhen , Chiu Jen-Fu , He Qing-Yu 
Published: November 2016

Abstract
Tumor metastasis is the dominant cause of death in cancer patients. However, the molecular and cellular mechanisms underlying tumor metastasis are still elusive. The identification of protein molecules with their expressions correlated to the metastatic process would help to understand the metastatic mechanisms and thus facilitate the development of strategies for the therapeutic interventions and clinical management of cancer. Proteomics is a systematic research approach aiming to provide the global characterization of protein expression and function under given conditions. Proteomic technology has been widely used in biomarker discovery and pathogenetic studies including tumor metastasis. This article provides a brief review of the application of proteomics in identifying molecular factors in tumor metastasis process. The combination of proteomics with other experimental approaches in biochemistry, cell biology, molecular genetics and chemistry, together with the development of new technologies and improvements in existing methodologies will continue to extend its application in studying cancer metastasis.
A Systematical Analysis of Tryptic Peptide Identification with Reverse Phase Liquid Chromatography and Electrospray Ion Trap Mass Spectrometry
Authors: Sun Wei , Wu Shuzhen , Wang Xiaorong , Zheng Dexian , Gao Youhe 
Published: November 2016

Abstract
In this study we systematically analyzed the elution condition of tryptic peptides and the characteristics of identified peptides in reverse phase liquid chromatography and electrospray tandem mass spectrometry (RPLC-MS/MS) analysis. Following protein digestion with trypsin, the peptide mixture was analyzed by on-line RPLC-MS/MS. Bovine serum albumin (BSA) was used to optimize acetonitrile (ACN) elution gradient for tryptic peptides, and Cytochrome C was used to retest the gradient and the sensitivity of LC-MS/MS. The characteristics of identified peptides were also analyzed. In our experiments, the suitable ACN gradient is 5% to 30% for tryptic peptide elution and the sensitivity of LC-MS/MS is 50 fmol. Analysis of the tryptic peptides demonstrated that longer (more than 10 amino acids) and multi-charge state (+2, +3) peptides are likely to be identified, and the hydropathicity of the peptides might not be related to whether it is more likely to be identified or not. The number of identified peptides for a protein might be used to estimate its loading amount under the same sample background. Moreover, in this study the identified peptides present three types of redundancy, namely identification, charge, and sequence redundancy, which may repress low abundance protein identification.
Predicting Protein Subcellular Localization: Past, Present, and Future
Authors: Dönnes Pierre , Höglund Annette 
Published: November 2016

Abstract
Functional characterization of every single protein is a major challenge of the post-genomic era. The large-scale analysis of a cell’s proteins, proteomics, seeks to provide these proteins with reliable annotations regarding their interaction partners and functions in the cellular machinery. An important step on this way is to determine the subcellular localization of each protein. Eukaryotic cells are divided into subcellular compartments, or organelles. Transport across the membrane into the organelles is a highly regulated and complex cellular process. Predicting the subcellular localization by computational means has been an area of vivid activity during recent years. The publicly available prediction methods differ mainly in four aspects: the underlying biological motivation, the computational method used, localization coverage, and reliability, which are of importance to the user. This review provides a short description of the main events in the protein sorting process and an overview of the most commonly used methods in this field.
A Brief Review of Computational Gene Prediction Methods
Authors: Wang Zhuo , Chen Yazhu , Li Yixue 
Published: November 2016

Abstract
With the development of genome sequencing for many organisms, more and more raw sequences need to be annotated. Gene prediction by computational methods for finding the location of protein coding regions is one of the essential issues in bioinformatics. Two classes of methods are generally adopted: similarity based searches and ab initio prediction. Here, we review the development of gene prediction methods, summarize the measures for evaluating predictor quality, highlight open problems in this area, and discuss future research directions.
Granulometric Analysis of Spots in DNA Microarray Images
Authors: Latha Behara , Venkatesh Balasubramanian 
Published: November 2016

Abstract
As the topological properties of each spot in DNA microarray images may vary from one another, we employed granulometries to understand the shape-size content contributed due to a significant intensity value within a spot. Analysis was performed on the microarray image that consisted of 240 spots by using concepts from mathematical morphology. In order to find out indices for each spot and to further classify them, we adopted morphological multiscale openings, which provided microarrays at multiple scales. Successive opened microarrays were subtracted to identify the protrusions that were smaller than the size of structuring element. Spot-wise details, in terms of probability of these observed protrusions, were computed by placing a regularly spaced grid on microarray such that each spot was centered in each grid. Based on the probability of size distribution functions of these protrusions isolated at each level, we estimated the mean size and texture index for each spot. With these characteristics, we classified the spots in a microarray image into bright and dull categories through pattern spectrum and shape-size complexity measures. These segregated spots can be compared with those of hybridization levels.
EST-Based Analysis of Gene Expression in the Porcine Brain
Authors: Zhang Bing , Jin Wu , Zeng Yanwu , Su Zhixi , Hu Songnian , Yu Jun 
Published: November 2016

Abstract
Since pig is an important livestock species worldwide, its gene expression has been investigated intensively, but rarely in brain. In order to study gene expression profiles in the pig central nervous system, we sequenced and analyzed 43,122 high-quality 5’ end expressed sequence tags (ESTs) from porcine cerebellum, cortex cerebrum, and brain stem cDNA libraries, involving several different prenatal and postnatal developmental stages. The initial ESTs were assembled into 16,101 clusters and compared to protein and nucleic acid databases in GenBank. Of these sequences, 30.6% clusters matched protein databases and represented function known sequences; 75.1% had significant hits to nucleic acid databases and partial represented known function; 73.3% matched known porcine ESTs; and 21.5% had no matches to any known sequences in GenBank. We used the categories defined by the Gene Ontology to survey gene expression in the porcine brain.
A Mitochondrial Genome Sequence of the Tibetan Antelope (Pantholops Hodgsonii)
Authors: Xu Shu-Qing , Yang Ying-Zhong , Zhou Jun , Jin Guo-En , Chen Yun-Tian , Wang Jun , Yang Huan-Ming , Wang Jian , Yu Jun , Zheng Xiao-Guang , Ge Ri-Li 
Published: November 2016

Abstract
To investigate genetic mechanisms of high altitude adaptations of native mammals on the Tibetan Plateau, we compared mitochondrial sequences of the endangered Pantholops hodgsonii with its lowland distant relatives Ovis aries and Capra hircus, as well as other mammals. The complete mitochondrial genome of P. hodgsonii (16,498 bp) revealed a similar gene order as of other mammals. Because of tandem duplications, the control region of P. hodgsonii mitochondrial genome is shorter than those of O. aries and C. hircus, but longer than those of Bos species. Phylogenetic analysis based on alignments of the entire cytochrome b genes suggested that P. hodgsonii is more closely related to O. aries and C. hircus, rather than to species of the Antilopinae subfamily. The estimated divergence time between P. hodgsonii and O. aries is about 2.25 million years ago. Further analysis on natural selection indicated that the COXI (cytochrome c oxidase subunit I) gene was under positive selection in P. hodgsonii and Bos grunniens. Considering the same climates and environments shared by these two mammalian species, we proposed that the mitochondrial COXI gene is probably relevant for these native mammals to adapt the high altitude environment unique to the Tibetan Plateau.
MicroRNA: Biological and Computational Perspective
Authors: Kong Yong , Han Jin-Hua 
Published: November 2016

Abstract
MicroRNAs (miRNAs) are endogenously expressed non-coding RNAs of 20–24 nucleotides, which post-transcriptionally regulate gene expression in plants and animals. Recently it has been recognized that miRNAs comprise one of the abundant gene families in multicellular species, and their regulatory functions in various biological processes are widely spread. There has been a surge in the research activities in this field in the past few years. From the very beginning, computational methods have been utilized as indispensable tools, and many discoveries have been obtained through combination of experimental and computational approaches. In this review, both biological and computational aspects of miRNA will be discussed. A brief history of the discovery of miRNA and discussion of microarray applications in miRNA research are also included.
The Evolutionary Relationship of the Domain Architectures in the RhoGEF-Containing Proteins
Authors: Sun Qing-Lan , Zhou Hong-Jun , Lin Kui 
Published: November 2016

Abstract
Domain insertions and deletions lead to variations in the domain architectures of the proteins from their common ancestor. In this work, we investigated four groups of the RhoGEF-containing proteins from different organisms with domain architectures RhoGEF-PH-SH3, SH3-RhoGEF-PH, RhoGEF-PH, and SH3-RhoGEF defined in the Pfam database. The phylogenetic trees were constructed using each individual domain and/or the combinations of all the domains. The phylogenetic analysis suggests that RhoGEF-PH-SH3 and SH3-RhoGEF-PH might have evolved from RhoGEF-PH through the insertion of SH3 independently, while SH3-RhoGEF of proteins in fruit fly might have evolved from SH3-RhoGEF-PH by the degeneration of PH domain.