VisANT: data-integrating visual framework for biological networks and modules

Hu, Zhenjun; Mellor, Joe; Wu, Jie; Yamada, Takuji; Holloway, Dustin T.; DeLisi, Charles

doi:10.1093/nar/gki431

Cited by 173 publications

(139 citation statements)

References 28 publications

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“…Gene Ontology and Network Analysis-A protein data set correlating with a specific factor was subjected to visANT (integrative visual analysis tool for biological networks and pathways, (62)) versus mouse databases. The generated network was analyzed using network analysis tools implemented in the Cytoscape software package (63).…”

Section: Data Acquisition and Peptide Identification Protein Abundancymentioning

confidence: 99%

Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation

Borovok

Nesher

Levin

et al. 2016

Molecular & Cellular Proteomics

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Spatial memory depends on the hippocampus, which is particularly vulnerable to aging. This vulnerability has implications for the impairment of navigation capacities in older people, who may show a marked drop in performance of spatial tasks with advancing age. Contemporary understanding of long-term memory formation relies on molecular mechanisms underlying long-term synaptic plasticity. With memory acquisition, activity-dependent changes occurring in synapses initiate multiple signal transduction pathways enhancing protein turnover. This enhancement facilitates de novo synthesis of plasticity related proteins, crucial factors for establishing persistent long-term synaptic plasticity and forming memory engrams. Extensive studies have been performed to elucidate molecular mechanisms of memory traces formation; however, the identity of plasticity related proteins is still evasive. In this study, we investigated protein turnover in mouse hippocampus during long-term spatial memory formation using the reference memory version of radial arm maze (RAM) paradigm. We identified 1592 proteins, which exhibited a complex picture of expression changes during spatial memory formation. Variable linear decomposition reduced significantly data dimensionality and enriched three principal factors responsible for variance of memory-related protein levels at (1) the initial phase of memory acquisition (165 proteins), (2) during the steep learning improvement (148 proteins), and (3) the final phase of the learning curve (123 proteins). Gene ontology and signaling pathways analysis revealed a clear correlation between memory improvement and learning phasecurbed expression profiles of proteins belonging to specific functional categories. We found differential enrichment of (1) Long-term synaptic plasticity is considered a cellular correlate of long-term memory (LTM) 1 . Contemporary understanding of memory formation is based on the initiation and maintenance of long-term synaptic plasticity (1-4), for which de novo protein synthesis is a vital requirement. De novo protein synthesis itself is secondary to activity-dependent changes in synapses that occur during learning processes. These activity changes trigger post-translational modifications of proteins initiating and sustaining multiple signal transduction pathways. In turn, these signaling pathways regulate changes in synaptic strength and connectivity by governing gene expression and protein translation (5-13). Depending on time elapsed since triggering of long-term synaptic plasticity, protein synthesis may be limited to the dendrites directly involved in the plasticity processes (14 -18). Multiple synaptic From the ‡Department

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Section: Data Acquisition and Peptide Identification Protein Abundancymentioning

confidence: 99%

Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation

Borovok

Nesher

Levin

et al. 2016

Molecular & Cellular Proteomics

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“…Plug-in such as NetworkAnalyzer (Assenov et al (2008)) computes some node centralities but does not allow direct integration with experimental data. Applications such as VisANT (Hu et al (2005)), and Centibin (Junker et al (2006)) calculate centralities, although they either calculate fewer centralities or are not suitable to integration with experimental data. Figure 1 shows a comparative evaluation of CentiScaPe and other applications.…”

Section: Centiscape a Software For Network Centralitiesmentioning

confidence: 99%

Centralities Based Analysis of Complex Networks

Scardoni¹,

Laudanna²

2012

New Frontiers in Graph Theory

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“…KEGG pathway analysis was performed with the protein-protein interaction network of the differential proteins in each group using Cytoscape (V2.8.2) with the ClueGO v1.4 plugin. A protein-protein interaction network was constructed using VisAnt toolkit (31,32), in which the differential proteins in each group served as a bait, and the proteins have a direct experimental interaction with the bait proteins in the databases. KEGG pathway was considered statistically significant when the corrected p value was less than 0.01.…”

Section: Fig 1 Ms/ms Spectra Used For the Identification And Quantimentioning

confidence: 99%

Identification of Candidate Biomarkers for Early Detection of Human Lung Squamous Cell Cancer by Quantitative Proteomics

Zeng

Zhang

Deng

et al. 2012

Molecular & Cellular Proteomics

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To discover novel biomarkers for early detection of human lung squamous cell cancer (LSCC) and explore possible mechanisms of LSCC carcinogenesis, iTRAQ-tagging combined with two dimensional liquid chromatography tandem MS analysis was used to identify differentially expressed proteins in human bronchial epithelial carcinogenic process using laser capture microdissection-purified normal bronchial epithelium (NBE), squamous metaplasia (SM), atypical hyperplasia (AH), carcinoma in situ (CIS) and invasive LSCC. As a result, 102 differentially expressed proteins were identified, and three differential proteins (GSTP1, HSPB1 and CKB) showing progressively expressional changes in the carcinogenic process were selectively validated by Western blotting. Immunohistochemistry was performed to detect the expression of the three proteins in an independent set of paraffinembedded archival specimens including various stage tissues of bronchial epithelial carcinogenesis, and their ability for early detection of LSCC was evaluated by receiver operating characteristic analysis. The results showed that the combination of the three proteins could perfectly discriminate NBE from preneoplastic lesions (SM, AH and CIS) from invasive LSCC, achieving a sensitivity of 96% and a specificity of 92% in discriminating NBE from preneoplatic lesions, a sensitivity of 100% and a specificity of 98% in discriminating NBE from invasive LSCC, and a sensitivity of 92% and a specificity of 91% in discriminating preneoplatic lesions from invasive LSCC, respectively. Furthermore, we knocked down GSTP1 in immortalized human bronchial epithelial cell line 16HBE cells, and then measured their susceptibility to carcinogen benzo ( Lung cancer is the most frequently occurring malignancy with increasing incidence and is the leading cause of mortality in cancer-related deaths in China and worldwide (1, 2). Although great improvement has been made in diagnosis and treatment of lung cancer, the overall patients' survival is still very low and does not exceed 15% (3). The poor prognosis of this cancer is mainly explained by the fact that the diagnosis is generally made only at advanced stages because of the lack of reliable, early diagnostic biomarkers and the limited understanding of its carcinogenic mechanisms. Therefore, identification of biomarkers for early detection of lung cancer is mandatory, in turn leading to more effective treatment and reduction of mortality.Lung squamous cell carcinoma (LSCC) 1 originated from the bronchial epithelial cells is the most common histological type of lung cancer. It is known that carcinogenesis of LSCC is a multistage process and the result of multistep accumulation of genetic and epigenetic alterations (4). With exposure to environmental carcinogens, bronchial epithelial carcinogenesis often progresses in the following manner: hyperplasia, squamous metaplasia (SM), atypical hyperplasia (AH), cancer in situ (CIS) and invasive cancer (5). LSCC is the end-point of a whole range of morphological abnormalities that are dis-...

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VisANT: data-integrating visual framework for biological networks and modules

Cited by 173 publications

References 28 publications

Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation

Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation

Centralities Based Analysis of Complex Networks

Identification of Candidate Biomarkers for Early Detection of Human Lung Squamous Cell Cancer by Quantitative Proteomics

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