PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: Symmetry preference in shapes, faces, flowers and landscapes
items: Identification and characterization of Gypsophila paniculata color morphs in Sleeping Bear Dunes National Lakeshore, MI, USA
items: iTRAQ-based quantitative proteome analysis reveals metabolic changes between a cleistogamous wheat mutant and its wild-type wheat counterpart
items: Characterization of bidirectional gene pairs in The Cancer Genome Atlas (TCGA) dataset
items: Worldwide scientific productions with immunotherapy of sepsis: a bibliometric analysis
items: A tropomyosin receptor kinase family protein, NTRK2 is a potential predictive biomarker for lung adenocarcinoma
items: An integration of deep learning with feature embedding for protein–protein interaction prediction
items: PhD7Faster 2.0: predicting clones propagating faster from the Ph.D.-7 phage display library by coupling PseAAC and tripeptide composition
items: Comprehensive analysis of an lncRNA-miRNA-mRNA competing endogenous RNA network in pulpitis
items: Coleoptera genome and transcriptome sequences reveal numerous differences in neuropeptide signaling between species

Symmetry preference in shapes, faces, flowers and landscapes
type: item
type: AcademicArticle
description: Most people like symmetry, and symmetry has been extensively used in visual art and architecture. In this study, we compared preference for images of abstract and familiar objects in the original format or when containing perfect bilateral symmetry. We created pairs of images for different categories: male faces, female faces, polygons, smoothed version of the polygons, flowers, and landscapes. This design allows us to compare symmetry preference in different domains. Each observer saw all categories randomly interleaved but saw only one of the two images in a pair. After recording preference, we recorded a rating of how salient the symmetry was for each image, and measured how quickly observers could decide which of the two images in a pair was symmetrical. Results reveal a general preference for symmetry in the case of shapes and faces. For landscapes, natural (no perfect symmetry) images were preferred. Correlations with judgments of saliency were present but generally low, and for landscapes the salience of symmetry was negatively related to preference. However, even within the category where symmetry was not liked (landscapes), the separate analysis of original and modified stimuli showed an interesting pattern: Salience of symmetry was correlated positively (artificial) or negatively (original) with preference, suggesting different effects of symmetry within the same class of stimuli based on context and categorization.
format: application/pdf
format: text/html
creator: Marco Bertamini
creator: Giulia Rampone
creator: Alexis D.J. Makin
creator: Andrew Jessop
subject: Psychiatry and Psychology
description: doi:10.7717/peerj.7078
publisher: PeerJ Inc.
rights: © 2019 Bertamini et al.
abstract: Most people like symmetry, and symmetry has been extensively used in visual art and architecture. In this study, we compared preference for images of abstract and familiar objects in the original format or when containing perfect bilateral symmetry. We created pairs of images for different categories: male faces, female faces, polygons, smoothed version of the polygons, flowers, and landscapes. This design allows us to compare symmetry preference in different domains. Each observer saw all categories randomly interleaved but saw only one of the two images in a pair. After recording preference, we recorded a rating of how salient the symmetry was for each image, and measured how quickly observers could decide which of the two images in a pair was symmetrical. Results reveal a general preference for symmetry in the case of shapes and faces. For landscapes, natural (no perfect symmetry) images were preferred. Correlations with judgments of saliency were present but generally low, and for landscapes the salience of symmetry was negatively related to preference. However, even within the category where symmetry was not liked (landscapes), the separate analysis of original and modified stimuli showed an interesting pattern: Salience of symmetry was correlated positively (artificial) or negatively (original) with preference, suggesting different effects of symmetry within the same class of stimuli based on context and categorization.
bibliographic citation: Bertamini et al. (2019) Symmetry preference in shapes, faces, flowers and landscapes. PeerJ 7:e7078 https://doi.org/10.7717/peerj.7078
date submitted: 2019-01-09
date accepted: 2019-05-06
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Bertamini
  given name: Marco
author list: Agent
  family name: Rampone
  given name: Giulia
author list: Agent
  family name: Makin
  given name: Alexis D.J.
author list: Agent
  family name: Jessop
  given name: Andrew
doi: 10.7717/peerj.7078
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 Bertamini et al.
attribution name: Bertamini et al.

Identification and characterization of Gypsophila paniculata color morphs in Sleeping Bear Dunes National Lakeshore, MI, USA
type: item
type: AcademicArticle
description: Background Gypsophila paniculata (baby’s breath) is an invasive species found throughout much of the northwest United States and western Canada. Recently, plants exhibiting a different color morphology were identified within the coastal dunes along eastern Lake Michigan. The common baby’s breath (G. paniculata) typically produces stems that are purple in color (purple morph), while the atypical morph has stems that are green-yellow (green-yellow morph). The purpose of this study was to characterize these newly identified morphs and determine if they are genetically distinct species from the common baby’s breath in order to assess whether alternative management strategies should be employed to control these populations. Methods We sequenced two chloroplast regions, ribulose-bisphosphate carboxylase gene (rbcL), and maturase K (matK), and one nuclear region, internal transcribed spacer 2 (ITS2), from the purple morphs and green-yellow morphs collected from Sleeping Bear Dunes National Lakeshore, MI, USA (SBDNL). Sequences were aligned to reference sequences from other Gypsophila species obtained from the Barcode of Life Database and GenBank databases. We also collected seeds from wild purple morph and wild green-yellow morph plants in SBDNL. We grew the seeds in a common garden setting and characterized the proportion of green-yellow individuals produced from the two color morphs after 5-months of growth. Results Phylogenetic analyses based upon rbcL, matK, and ITS2 regions suggest that the two color morphs are not distinct species and they both belong to G. paniculata. Seeds collected from wild green-yellow morphs produced a significantly higher proportion of green-yellow individuals compared to the number produced by seeds collected from wild purple morphs. However, seeds collected from both color morphs produced more purple morphs than green-yellow morphs. Discussion Based upon these results, we propose that the two color morphs are variants of G. paniculata. Given…
format: application/pdf
format: text/html
creator: Marisa L. Yang
creator: Emma Rice
creator: Hailee Leimbach-Maus
creator: Charlyn G. Partridge
subject: Conservation Biology
subject: Plant Science
description: doi:10.7717/peerj.7100
publisher: PeerJ Inc.
rights: © 2019 Yang et al.
abstract: Background Gypsophila paniculata (baby’s breath) is an invasive species found throughout much of the northwest United States and western Canada. Recently, plants exhibiting a different color morphology were identified within the coastal dunes along eastern Lake Michigan. The common baby’s breath (G. paniculata) typically produces stems that are purple in color (purple morph), while the atypical morph has stems that are green-yellow (green-yellow morph). The purpose of this study was to characterize these newly identified morphs and determine if they are genetically distinct species from the common baby’s breath in order to assess whether alternative management strategies should be employed to control these populations. Methods We sequenced two chloroplast regions, ribulose-bisphosphate carboxylase gene (rbcL), and maturase K (matK), and one nuclear region, internal transcribed spacer 2 (ITS2), from the purple morphs and green-yellow morphs collected from Sleeping Bear Dunes National Lakeshore, MI, USA (SBDNL). Sequences were aligned to reference sequences from other Gypsophila species obtained from the Barcode of Life Database and GenBank databases. We also collected seeds from wild purple morph and wild green-yellow morph plants in SBDNL. We grew the seeds in a common garden setting and characterized the proportion of green-yellow individuals produced from the two color morphs after 5-months of growth. Results Phylogenetic analyses based upon rbcL, matK, and ITS2 regions suggest that the two color morphs are not distinct species and they both belong to G. paniculata. Seeds collected from wild green-yellow morphs produced a significantly higher proportion of green-yellow individuals compared to the number produced by seeds collected from wild purple morphs. However, seeds collected from both color morphs produced more purple morphs than green-yellow morphs. Discussion Based upon these results, we propose that the two color morphs are variants of G. paniculata. Given…
bibliographic citation: Yang et al. (2019) Identification and characterization of Gypsophila paniculata color morphs in Sleeping Bear Dunes National Lakeshore, MI, USA. PeerJ 7:e7100 https://doi.org/10.7717/peerj.7100
date submitted: 2018-03-14
date accepted: 2019-05-08
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Yang
  given name: Marisa L.
author list: Agent
  family name: Rice
  given name: Emma
author list: Agent
  family name: Leimbach-Maus
  given name: Hailee
author list: Agent
  family name: Partridge
  given name: Charlyn G.
doi: 10.7717/peerj.7100
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 Yang et al.
attribution name: Yang et al.

iTRAQ-based quantitative proteome analysis reveals metabolic changes between a cleistogamous wheat mutant and its wild-type wheat counterpart
type: item
type: AcademicArticle
description: Background Wheat is one of the most important staple crops worldwide. Fusarium head blight (FHB) severely affects wheat yield and quality. A novel bread wheat mutant, ZK001, characterized as cleistogamic was isolated from a non-cleistogamous variety Yumai 18 (YM18) through static magnetic field mutagenesis. Cleistogamy is a promising strategy for controlling FHB. However, little is known about the mechanism of cleistogamy in wheat. Methods We performed a FHB resistance test to identify the FHB infection rate of ZK001. We also measured the agronomic traits of ZK001 and the starch and total soluble sugar contents of lodicules in YM18 and ZK001. Finally, we performed comparative studies at the proteome level between YM18 and ZK001 based on the proteomic technique of isobaric tags for relative and absolute quantification. Results The infection rate of ZK001 was lower than that of its wild-type and Aikang 58. The abnormal lodicules of ZK001 lost the ability to push the lemma and palea apart during the flowering stage. Proteome analysis showed that the main differentially abundant proteins (DAPs) were related to carbohydrate metabolism, protein transport, and calcium ion binding. These DAPs may work together to regulate cellular homeostasis, osmotic pressure and the development of lodicules. This hypothesis is supported by the analysis of starch, soluble sugar content in the lodicules as well as the results of Quantitative reverse transcription polymerase chain reaction. Conclusions Proteomic analysis has provided comprehensive information that should be useful for further research on the lodicule development mechanism in wheat. The ZK001 mutant is optimal for studying flower development in wheat and could be very important for FHB resistant projects via conventional crossing.
format: application/pdf
format: text/html
creator: Caiguo Tang
creator: Huilan Zhang
creator: Pingping Zhang
creator: Yuhan Ma
creator: Minghui Cao
creator: Hao Hu
creator: Faheem Afzal Shah
creator: Weiwei Zhao
creator: Minghao Li
creator: Lifang Wu
subject: Molecular Biology
subject: Plant Science
description: doi:10.7717/peerj.7104
publisher: PeerJ Inc.
rights: © 2019 Tang et al.
abstract: Background Wheat is one of the most important staple crops worldwide. Fusarium head blight (FHB) severely affects wheat yield and quality. A novel bread wheat mutant, ZK001, characterized as cleistogamic was isolated from a non-cleistogamous variety Yumai 18 (YM18) through static magnetic field mutagenesis. Cleistogamy is a promising strategy for controlling FHB. However, little is known about the mechanism of cleistogamy in wheat. Methods We performed a FHB resistance test to identify the FHB infection rate of ZK001. We also measured the agronomic traits of ZK001 and the starch and total soluble sugar contents of lodicules in YM18 and ZK001. Finally, we performed comparative studies at the proteome level between YM18 and ZK001 based on the proteomic technique of isobaric tags for relative and absolute quantification. Results The infection rate of ZK001 was lower than that of its wild-type and Aikang 58. The abnormal lodicules of ZK001 lost the ability to push the lemma and palea apart during the flowering stage. Proteome analysis showed that the main differentially abundant proteins (DAPs) were related to carbohydrate metabolism, protein transport, and calcium ion binding. These DAPs may work together to regulate cellular homeostasis, osmotic pressure and the development of lodicules. This hypothesis is supported by the analysis of starch, soluble sugar content in the lodicules as well as the results of Quantitative reverse transcription polymerase chain reaction. Conclusions Proteomic analysis has provided comprehensive information that should be useful for further research on the lodicule development mechanism in wheat. The ZK001 mutant is optimal for studying flower development in wheat and could be very important for FHB resistant projects via conventional crossing.
bibliographic citation: Tang et al. (2019) iTRAQ-based quantitative proteome analysis reveals metabolic changes between a cleistogamous wheat mutant and its wild-type wheat counterpart. PeerJ 7:e7104 https://doi.org/10.7717/peerj.7104
date submitted: 2019-01-06
date accepted: 2019-05-08
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tang
  given name: Caiguo
author list: Agent
  family name: Zhang
  given name: Huilan
author list: Agent
  family name: Zhang
  given name: Pingping
author list: Agent
  family name: Ma
  given name: Yuhan
author list: Agent
  family name: Cao
  given name: Minghui
author list: Agent
  family name: Hu
  given name: Hao
author list: Agent
  family name: Shah
  given name: Faheem Afzal
author list: Agent
  family name: Zhao
  given name: Weiwei
author list: Agent
  family name: Li
  given name: Minghao
author list: Agent
  family name: Wu
  given name: Lifang
doi: 10.7717/peerj.7104
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 Tang et al.
attribution name: Tang et al.

Characterization of bidirectional gene pairs in The Cancer Genome Atlas (TCGA) dataset
type: item
type: AcademicArticle
description: The “bidirectional gene pair” indicates a particular head-to-head gene organization in which transcription start sites of two genes are located on opposite strands of genomic DNA within a region of one kb. Despite bidirectional gene pairs are well characterized, little is known about their expression profiles and regulation features in tumorigenesis. We used RNA-seq data from The Cancer Genome Atlas (TCGA) dataset for a systematic analysis of the expression profiles of bidirectional gene pairs in 13 cancer datasets. Gene pairs on the opposite strand with transcription end site distance within one kb or on the same strand with the distance of two genes between 1–10 kb and gene pairs comprising two randomly chosen genes were used as control gene pairs (CG1, CG2, and random). We identified and characterized up-/down-regulated genes by comparing the expression level between tumors and adjacent normal tissues in 13 TCGA datasets. There were no consistently significant difference in the percentage of up-/down-regulated genes between bidirectional and control/random genes in most of TCGA datasets. However, the percentage of bidirectional gene pairs comprising two up- or two down-regulated genes was significantly higher than gene pairs from CG1/2 in 12/11 analyzed TCGA datasets and the random gene pairs in all 13 TCGA datasets. Then we identified the methylation correlated bidirectional genes to explore the regulatory mechanism of bidirectional genes. Like the differentially expressed gene pairs, the bidirectional genes in a pair were significantly prone to be both hypo- or hyper-methylation correlated genes in 12/13 TCGA datasets when comparing to the CG2/random gene pairs despite no significant difference between the percentages of hypo-/hyper-methylation correlated genes in bidirectional and CG2/random genes in most of TCGA datasets. Finally, we explored the correlation between bidirectional genes and patient’s survival, identifying prognostic bidirectional genes and pro…
format: application/pdf
format: text/html
creator: Juchuanli Tu
creator: Xiaolu Li
creator: Jianjun Wang
subject: Bioinformatics
subject: Genomics
description: doi:10.7717/peerj.7107
publisher: PeerJ Inc.
rights: © 2019 Tu et al.
abstract: The “bidirectional gene pair” indicates a particular head-to-head gene organization in which transcription start sites of two genes are located on opposite strands of genomic DNA within a region of one kb. Despite bidirectional gene pairs are well characterized, little is known about their expression profiles and regulation features in tumorigenesis. We used RNA-seq data from The Cancer Genome Atlas (TCGA) dataset for a systematic analysis of the expression profiles of bidirectional gene pairs in 13 cancer datasets. Gene pairs on the opposite strand with transcription end site distance within one kb or on the same strand with the distance of two genes between 1–10 kb and gene pairs comprising two randomly chosen genes were used as control gene pairs (CG1, CG2, and random). We identified and characterized up-/down-regulated genes by comparing the expression level between tumors and adjacent normal tissues in 13 TCGA datasets. There were no consistently significant difference in the percentage of up-/down-regulated genes between bidirectional and control/random genes in most of TCGA datasets. However, the percentage of bidirectional gene pairs comprising two up- or two down-regulated genes was significantly higher than gene pairs from CG1/2 in 12/11 analyzed TCGA datasets and the random gene pairs in all 13 TCGA datasets. Then we identified the methylation correlated bidirectional genes to explore the regulatory mechanism of bidirectional genes. Like the differentially expressed gene pairs, the bidirectional genes in a pair were significantly prone to be both hypo- or hyper-methylation correlated genes in 12/13 TCGA datasets when comparing to the CG2/random gene pairs despite no significant difference between the percentages of hypo-/hyper-methylation correlated genes in bidirectional and CG2/random genes in most of TCGA datasets. Finally, we explored the correlation between bidirectional genes and patient’s survival, identifying prognostic bidirectional genes and pro…
bibliographic citation: Tu et al. (2019) Characterization of bidirectional gene pairs in The Cancer Genome Atlas (TCGA) dataset. PeerJ 7:e7107 https://doi.org/10.7717/peerj.7107
date submitted: 2019-02-15
date accepted: 2019-05-09
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tu
  given name: Juchuanli
author list: Agent
  family name: Li
  given name: Xiaolu
author list: Agent
  family name: Wang
  given name: Jianjun
doi: 10.7717/peerj.7107
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 Tu et al.
attribution name: Tu et al.

Worldwide scientific productions with immunotherapy of sepsis: a bibliometric analysis
type: item
type: AcademicArticle
description: Background Sepsis represents a significant healthcare problem worldwide and causes a high number of deaths every year but remains to be fully understood. During and after sepsis, the host immune response is complex and involves an initial excessive host inflammatory response to infection that is closely related to tissue damage and leads to organ failure. Over the past three decades, immunotherapy for sepsis has vastly improved, but in this area, the most influential articles, journals, authors, and countries have not yet been completely summarized and analyzed. Objective Performed a bibliometric analysis on all the articles concerning immunotherapy for sepsis from 1962 to 2019 was our objective, and we also explored the potential correlations between publications of different countries and their gross domestic product (GDP). Methods All articles about immunotherapy for sepsis were extracted from the Scopus database and analyzed. We also retrieved GDP data from all the countries that have published information from the World Bank. Results In summary, we have retrieved 1,483 related articles from the Scopus database starting from the first publication on immunotherapy for sepsis in 1962 through March 16, 2019. Over the past decade, the number of the articles published has increased year by year to reach 866 in total, which accounts for about 58% of all publications, with 2017 being the most prolific year when 179 articles were published. The US published 604 articles (41%), followed by China (n = 163, 11%), and Germany (n = 158, 11%). In terms of publishing media, the journal that published the highest number of the articles was Journal of Critical Care Medicine with 65 articles (4%), followed by Shock with 55 articles (4%), and Critical Care with 35 articles (2%). There was a strong correlation between the GDP of the different countries and their publication numbers (r = 0.811, P < 0.001). Conclusions Our present study analyzed all types of articles concerning immun…
format: application/pdf
format: text/html
creator: Ronghao Wan
creator: Lei Li
creator: Chenwei Xing
creator: Ronggang Peng
creator: Liang Gao
subject: Emergency and Critical Care
subject: Hematology
subject: Immunology
subject: Infectious Diseases
description: doi:10.7717/peerj.7116
publisher: PeerJ Inc.
rights: © 2019 Wan et al.
abstract: Background Sepsis represents a significant healthcare problem worldwide and causes a high number of deaths every year but remains to be fully understood. During and after sepsis, the host immune response is complex and involves an initial excessive host inflammatory response to infection that is closely related to tissue damage and leads to organ failure. Over the past three decades, immunotherapy for sepsis has vastly improved, but in this area, the most influential articles, journals, authors, and countries have not yet been completely summarized and analyzed. Objective Performed a bibliometric analysis on all the articles concerning immunotherapy for sepsis from 1962 to 2019 was our objective, and we also explored the potential correlations between publications of different countries and their gross domestic product (GDP). Methods All articles about immunotherapy for sepsis were extracted from the Scopus database and analyzed. We also retrieved GDP data from all the countries that have published information from the World Bank. Results In summary, we have retrieved 1,483 related articles from the Scopus database starting from the first publication on immunotherapy for sepsis in 1962 through March 16, 2019. Over the past decade, the number of the articles published has increased year by year to reach 866 in total, which accounts for about 58% of all publications, with 2017 being the most prolific year when 179 articles were published. The US published 604 articles (41%), followed by China (n = 163, 11%), and Germany (n = 158, 11%). In terms of publishing media, the journal that published the highest number of the articles was Journal of Critical Care Medicine with 65 articles (4%), followed by Shock with 55 articles (4%), and Critical Care with 35 articles (2%). There was a strong correlation between the GDP of the different countries and their publication numbers (r = 0.811, P < 0.001). Conclusions Our present study analyzed all types of articles concerning immun…
bibliographic citation: Wan et al. (2019) Worldwide scientific productions with immunotherapy of sepsis: a bibliometric analysis. PeerJ 7:e7116 https://doi.org/10.7717/peerj.7116
date submitted: 2019-02-01
date accepted: 2019-05-11
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Wan
  given name: Ronghao
author list: Agent
  family name: Li
  given name: Lei
author list: Agent
  family name: Xing
  given name: Chenwei
author list: Agent
  family name: Peng
  given name: Ronggang
author list: Agent
  family name: Gao
  given name: Liang
doi: 10.7717/peerj.7116
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 Wan et al.
attribution name: Wan et al.

A tropomyosin receptor kinase family protein, NTRK2 is a potential predictive biomarker for lung adenocarcinoma
type: item
type: AcademicArticle
description: Neurotrophic receptor tyrosine kinase 2 (NTRK2) is a member of the tropomyosin receptor kinase family associated with the tumor development. However, the detailed function of NTRK2 in lung cancer, especially in lung adenocarcinoma (LUAD), is still not fully understood. Here, we investigated the effects of NTRK2 on LUAD biology. Through analyzing bioinformatics data derived from several databases, such as Oncomine, Gene Expression Profiling Interactive Analysis and UALCAN, we found that NTRK2 expression was significantly decreased in LUAD tissues. Clinical data acquired from Wanderer database, which is linked to The Cancer Genome Atlas database, demonstrated that the expression and methylation site of NTRK2 were significantly related to the clinical characteristics and prognosis of LUAD. Furthermore, NTRK2 expression was increased remarkably after treatment with the protein kinase B (AKT) inhibitor MK2206 and the anticancer agent actinomycin D. Functional enrichment analysis of NTRK2-associated coexpression genes was further conducted. Together, our results suggested that downregulated NTRK2 might be used in the diagnostic and prognostic evaluation of LUAD patients, or as a potential therapeutic target for the treatment of LUAD.
format: application/pdf
format: text/html
creator: Xiang Wang
creator: Zhijie Xu
creator: Xi Chen
creator: Xinxin Ren
creator: Jie Wei
creator: Shuyi Zhou
creator: Xue Yang
creator: Shuangshuang Zeng
creator: Long Qian
creator: Geting Wu
creator: Zhicheng Gong
creator: Yuanliang Yan
subject: Bioinformatics
subject: Oncology
subject: Pharmacology
subject: Respiratory Medicine
description: doi:10.7717/peerj.7125
publisher: PeerJ Inc.
rights: © 2019 Wang et al.
abstract: Neurotrophic receptor tyrosine kinase 2 (NTRK2) is a member of the tropomyosin receptor kinase family associated with the tumor development. However, the detailed function of NTRK2 in lung cancer, especially in lung adenocarcinoma (LUAD), is still not fully understood. Here, we investigated the effects of NTRK2 on LUAD biology. Through analyzing bioinformatics data derived from several databases, such as Oncomine, Gene Expression Profiling Interactive Analysis and UALCAN, we found that NTRK2 expression was significantly decreased in LUAD tissues. Clinical data acquired from Wanderer database, which is linked to The Cancer Genome Atlas database, demonstrated that the expression and methylation site of NTRK2 were significantly related to the clinical characteristics and prognosis of LUAD. Furthermore, NTRK2 expression was increased remarkably after treatment with the protein kinase B (AKT) inhibitor MK2206 and the anticancer agent actinomycin D. Functional enrichment analysis of NTRK2-associated coexpression genes was further conducted. Together, our results suggested that downregulated NTRK2 might be used in the diagnostic and prognostic evaluation of LUAD patients, or as a potential therapeutic target for the treatment of LUAD.
bibliographic citation: Wang et al. (2019) A tropomyosin receptor kinase family protein, NTRK2 is a potential predictive biomarker for lung adenocarcinoma. PeerJ 7:e7125 https://doi.org/10.7717/peerj.7125
date submitted: 2019-02-11
date accepted: 2019-05-14
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Wang
  given name: Xiang
author list: Agent
  family name: Xu
  given name: Zhijie
author list: Agent
  family name: Chen
  given name: Xi
author list: Agent
  family name: Ren
  given name: Xinxin
author list: Agent
  family name: Wei
  given name: Jie
author list: Agent
  family name: Zhou
  given name: Shuyi
author list: Agent
  family name: Yang
  given name: Xue
author list: Agent
  family name: Zeng
  given name: Shuangshuang
author list: Agent
  family name: Qian
  given name: Long
author list: Agent
  family name: Wu
  given name: Geting
author list: Agent
  family name: Gong
  given name: Zhicheng
author list: Agent
  family name: Yan
  given name: Yuanliang
doi: 10.7717/peerj.7125
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 Wang et al.
attribution name: Wang et al.

An integration of deep learning with feature embedding for protein–protein interaction prediction
type: item
type: AcademicArticle
description: Protein–protein interactions are closely relevant to protein function and drug discovery. Hence, accurately identifying protein–protein interactions will help us to understand the underlying molecular mechanisms and significantly facilitate the drug discovery. However, the majority of existing computational methods for protein–protein interactions prediction are focused on the feature extraction and combination of features and there have been limited gains from the state-of-the-art models. In this work, a new residue representation method named Res2vec is designed for protein sequence representation. Residue representations obtained by Res2vec describe more precisely residue-residue interactions from raw sequence and supply more effective inputs for the downstream deep learning model. Combining effective feature embedding with powerful deep learning techniques, our method provides a general computational pipeline to infer protein–protein interactions, even when protein structure knowledge is entirely unknown. The proposed method DeepFE-PPI is evaluated on the S. Cerevisiae and human datasets. The experimental results show that DeepFE-PPI achieves 94.78% (accuracy), 92.99% (recall), 96.45% (precision), 89.62% (Matthew’s correlation coefficient, MCC) and 98.71% (accuracy), 98.54% (recall), 98.77% (precision), 97.43% (MCC), respectively. In addition, we also evaluate the performance of DeepFE-PPI on five independent species datasets and all the results are superior to the existing methods. The comparisons show that DeepFE-PPI is capable of predicting protein–protein interactions by a novel residue representation method and a deep learning classification framework in an acceptable level of accuracy. The codes along with instructions to reproduce this work are available from https://github.com/xal2019/DeepFE-PPI.
format: application/pdf
format: text/html
creator: Yu Yao
creator: Xiuquan Du
creator: Yanyu Diao
creator: Huaixu Zhu
subject: Bioinformatics
subject: Computational Biology
subject: Data Mining and Machine Learning
description: doi:10.7717/peerj.7126
publisher: PeerJ Inc.
rights: © 2019 Yao et al.
abstract: Protein–protein interactions are closely relevant to protein function and drug discovery. Hence, accurately identifying protein–protein interactions will help us to understand the underlying molecular mechanisms and significantly facilitate the drug discovery. However, the majority of existing computational methods for protein–protein interactions prediction are focused on the feature extraction and combination of features and there have been limited gains from the state-of-the-art models. In this work, a new residue representation method named Res2vec is designed for protein sequence representation. Residue representations obtained by Res2vec describe more precisely residue-residue interactions from raw sequence and supply more effective inputs for the downstream deep learning model. Combining effective feature embedding with powerful deep learning techniques, our method provides a general computational pipeline to infer protein–protein interactions, even when protein structure knowledge is entirely unknown. The proposed method DeepFE-PPI is evaluated on the S. Cerevisiae and human datasets. The experimental results show that DeepFE-PPI achieves 94.78% (accuracy), 92.99% (recall), 96.45% (precision), 89.62% (Matthew’s correlation coefficient, MCC) and 98.71% (accuracy), 98.54% (recall), 98.77% (precision), 97.43% (MCC), respectively. In addition, we also evaluate the performance of DeepFE-PPI on five independent species datasets and all the results are superior to the existing methods. The comparisons show that DeepFE-PPI is capable of predicting protein–protein interactions by a novel residue representation method and a deep learning classification framework in an acceptable level of accuracy. The codes along with instructions to reproduce this work are available from https://github.com/xal2019/DeepFE-PPI.
bibliographic citation: Yao et al. (2019) An integration of deep learning with feature embedding for protein–protein interaction prediction. PeerJ 7:e7126 https://doi.org/10.7717/peerj.7126
date submitted: 2018-04-18
date accepted: 2019-05-14
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Yao
  given name: Yu
author list: Agent
  family name: Du
  given name: Xiuquan
author list: Agent
  family name: Diao
  given name: Yanyu
author list: Agent
  family name: Zhu
  given name: Huaixu
doi: 10.7717/peerj.7126
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: ©2019 Yao et al.
attribution name: Yao et al.

PhD7Faster 2.0: predicting clones propagating faster from the Ph.D.-7 phage display library by coupling PseAAC and tripeptide composition
type: item
type: AcademicArticle
description: Selection from phage display libraries empowers isolation of high-affinity ligands for various targets. However, this method also identifies propagation-related target-unrelated peptides (PrTUPs). These false positive hits appear because of their amplification advantages. In this report, we present PhD7Faster 2.0 for predicting fast-propagating clones from the Ph.D.-7 phage display library, which was developed based on the support vector machine. Feature selection was performed against PseAAC and tripeptide composition using the incremental feature selection method. Ten-fold cross-validation results show that PhD7Faster 2.0 succeeds a decent performance with the accuracy of 81.84%, the Matthews correlation coefficient of 0.64 and the area under the ROC curve of 0.90. The permutation test with 1,000 shuffles resulted in p < 0.001. We implemented PhD7Faster 2.0 into a publicly accessible web tool (http://i.uestc.edu.cn/sarotup3/cgi-bin/PhD7Faster.pl) and constructed standalone graphical user interface and command-line versions for different systems. The standalone PhD7Faster 2.0 is able to detect PrTUPs within small datasets as well as large-scale datasets. This makes PhD7Faster 2.0 an enhanced and powerful tool for scanning and reporting faster-growing clones from the Ph.D.-7 phage display library.
format: application/pdf
format: text/html
creator: Bifang He
creator: Heng Chen
creator: Jian Huang
subject: Bioinformatics
subject: Data Mining and Machine Learning
description: doi:10.7717/peerj.7131
publisher: PeerJ Inc.
rights: © 2019 He et al.
abstract: Selection from phage display libraries empowers isolation of high-affinity ligands for various targets. However, this method also identifies propagation-related target-unrelated peptides (PrTUPs). These false positive hits appear because of their amplification advantages. In this report, we present PhD7Faster 2.0 for predicting fast-propagating clones from the Ph.D.-7 phage display library, which was developed based on the support vector machine. Feature selection was performed against PseAAC and tripeptide composition using the incremental feature selection method. Ten-fold cross-validation results show that PhD7Faster 2.0 succeeds a decent performance with the accuracy of 81.84%, the Matthews correlation coefficient of 0.64 and the area under the ROC curve of 0.90. The permutation test with 1,000 shuffles resulted in p < 0.001. We implemented PhD7Faster 2.0 into a publicly accessible web tool (http://i.uestc.edu.cn/sarotup3/cgi-bin/PhD7Faster.pl) and constructed standalone graphical user interface and command-line versions for different systems. The standalone PhD7Faster 2.0 is able to detect PrTUPs within small datasets as well as large-scale datasets. This makes PhD7Faster 2.0 an enhanced and powerful tool for scanning and reporting faster-growing clones from the Ph.D.-7 phage display library.
bibliographic citation: He et al. (2019) PhD7Faster 2.0: predicting clones propagating faster from the Ph.D.-7 phage display library by coupling PseAAC and tripeptide composition. PeerJ 7:e7131 https://doi.org/10.7717/peerj.7131
date submitted: 2018-12-22
date accepted: 2019-05-15
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: He
  given name: Bifang
author list: Agent
  family name: Chen
  given name: Heng
author list: Agent
  family name: Huang
  given name: Jian
doi: 10.7717/peerj.7131
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 He et al.
attribution name: He et al.

Comprehensive analysis of an lncRNA-miRNA-mRNA competing endogenous RNA network in pulpitis
type: item
type: AcademicArticle
description: Background Pulpitis is a common inflammatory disease that affects dental pulp. It is important to understand the molecular signals of inflammation and repair associated with this process. Increasing evidence has revealed that long noncoding RNAs (lncRNAs), via competitively sponging microRNAs (miRNAs), can act as competing endogenous RNAs (ceRNAs) to regulate inflammation and reparative responses. The aim of this study was to elucidate the potential roles of lncRNA, miRNA and messenger RNA (mRNA) ceRNA networks in pulpitis tissues compared to normal control tissues. Methods The oligo and limma packages were used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively) based on expression profiles in two datasets, GSE92681 and GSE77459, from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) networks and modules were established to screen hub genes using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) plugin for Cytoscape, respectively. Furthermore, an lncRNA-miRNA-mRNA-hub genes regulatory network was constructed to investigate mechanisms related to the progression and prognosis of pulpitis. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify critical lncRNAs that may significantly affect the pathogenesis in inflamed and normal human dental pulp. Results A total of 644 upregulated and 264 downregulated differentially expressed genes (DEGs) in pulpitis samples were identified from the GSE77459 dataset, while 8 up- and 19 downregulated probes associated with lncRNA were identified from the GSE92681 dataset. Protein–protein interaction (PPI) based on STRING analysis revealed a network of DEGs containing 4,929 edges and 623 nodes. Upon combined an…
format: application/pdf
format: text/html
creator: Fangcao Lei
creator: Han Zhang
creator: Xiaoli Xie
subject: Bioinformatics
subject: Dentistry
description: doi:10.7717/peerj.7135
publisher: PeerJ Inc.
rights: © 2019 Lei et al.
abstract: Background Pulpitis is a common inflammatory disease that affects dental pulp. It is important to understand the molecular signals of inflammation and repair associated with this process. Increasing evidence has revealed that long noncoding RNAs (lncRNAs), via competitively sponging microRNAs (miRNAs), can act as competing endogenous RNAs (ceRNAs) to regulate inflammation and reparative responses. The aim of this study was to elucidate the potential roles of lncRNA, miRNA and messenger RNA (mRNA) ceRNA networks in pulpitis tissues compared to normal control tissues. Methods The oligo and limma packages were used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively) based on expression profiles in two datasets, GSE92681 and GSE77459, from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) networks and modules were established to screen hub genes using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) plugin for Cytoscape, respectively. Furthermore, an lncRNA-miRNA-mRNA-hub genes regulatory network was constructed to investigate mechanisms related to the progression and prognosis of pulpitis. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify critical lncRNAs that may significantly affect the pathogenesis in inflamed and normal human dental pulp. Results A total of 644 upregulated and 264 downregulated differentially expressed genes (DEGs) in pulpitis samples were identified from the GSE77459 dataset, while 8 up- and 19 downregulated probes associated with lncRNA were identified from the GSE92681 dataset. Protein–protein interaction (PPI) based on STRING analysis revealed a network of DEGs containing 4,929 edges and 623 nodes. Upon combined an…
bibliographic citation: Lei et al. (2019) Comprehensive analysis of an lncRNA-miRNA-mRNA competing endogenous RNA network in pulpitis. PeerJ 7:e7135 https://doi.org/10.7717/peerj.7135
date submitted: 2019-02-20
date accepted: 2019-05-16
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Lei
  given name: Fangcao
author list: Agent
  family name: Zhang
  given name: Han
author list: Agent
  family name: Xie
  given name: Xiaoli
doi: 10.7717/peerj.7135
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: ©2019 Lei et al.
attribution name: Lei et al.

Coleoptera genome and transcriptome sequences reveal numerous differences in neuropeptide signaling between species
type: item
type: AcademicArticle
description: Background Insect neuropeptides are interesting for the potential their receptors hold as plausible targets for a novel generation of pesticides. Neuropeptide genes have been identified in a number of different species belonging to a variety of insects. Results suggest significant neuropeptide variation between different orders, but much less is known of neuropeptidome variability within an insect order. I therefore compared the neuropeptidomes of a number of Coleoptera. Methodology Publicly available genome sequences, transcriptomes and the original sequence data in the form of short sequence read archives were analyzed for the presence or absence of genes coding neuropeptides as well as some neuropeptide receptors in seventeen beetle species. Results Significant differences exist between the Coleoptera analyzed here, while many neuropeptides that were previously characterized from Tribolium castaneum appear very similar in all species, some are not and others are lacking in one or more species. On the other hand, leucokinin, which was presumed to be universally absent from Coleoptera, is still present in non-Polyphaga beetles. Conclusion The variability in neuropeptidome composition between species from the same insect order may be as large as the one that exists between species from different orders.
format: application/pdf
format: text/html
creator: Jan A. Veenstra
subject: Bioinformatics
subject: Entomology
subject: Genomics
subject: Neuroscience
subject: Zoology
description: doi:10.7717/peerj.7144
publisher: PeerJ Inc.
rights: © 2019 Veenstra
abstract: Background Insect neuropeptides are interesting for the potential their receptors hold as plausible targets for a novel generation of pesticides. Neuropeptide genes have been identified in a number of different species belonging to a variety of insects. Results suggest significant neuropeptide variation between different orders, but much less is known of neuropeptidome variability within an insect order. I therefore compared the neuropeptidomes of a number of Coleoptera. Methodology Publicly available genome sequences, transcriptomes and the original sequence data in the form of short sequence read archives were analyzed for the presence or absence of genes coding neuropeptides as well as some neuropeptide receptors in seventeen beetle species. Results Significant differences exist between the Coleoptera analyzed here, while many neuropeptides that were previously characterized from Tribolium castaneum appear very similar in all species, some are not and others are lacking in one or more species. On the other hand, leucokinin, which was presumed to be universally absent from Coleoptera, is still present in non-Polyphaga beetles. Conclusion The variability in neuropeptidome composition between species from the same insect order may be as large as the one that exists between species from different orders.
bibliographic citation: Veenstra (2019) Coleoptera genome and transcriptome sequences reveal numerous differences in neuropeptide signaling between species. PeerJ 7:e7144 https://doi.org/10.7717/peerj.7144
date submitted: 2019-03-01
date accepted: 2019-05-16
issued: 2019-06-17
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Veenstra
  given name: Jan A.
doi: 10.7717/peerj.7144
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-06-17
copyright: © 2019 Veenstra
attribution name: Veenstra

PeerJ
type: Periodical
uri: PeerJ
issn: 2167-8359