Human Protein Reference Database--2009 update

Prasad, T. S. Keshava; Goel, Renu; Kandasamy, Kumaran; Keerthikumar, Shivakumar; Kumar, Sameer; Mathivanan, Suresh; Telikicherla, Deepthi; Raju, Rajesh; Shafreen, Beema; Venugopal, Abhilash; Balakrishnan, Lavanya; Marimuthu, Arivusudar; Banerjee, Sutopa; Somanathan, Devi S.; Sebastian, Aimy; Rani, Sandhya; Ray, Somak; Kishore, Charles Jacob Harrys; Kanth, Sashi; Ahmed, Mukhtar; Kashyap, Manoj Kumar; Mohmood, Riaz; Ramachandra, Y. L.; Krishna, V.; Rahiman, B. Abdul; Mohan, S. Sujatha; Ranganathan, Prathibha; Ramabadran, Subhashri; Chaerkady, Raghothama; Pandey, Akhilesh

doi:10.1093/nar/gkn892

Cited by 2,808 publications

(1,775 citation statements)

References 24 publications

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“…16,50 Pathway analysis was done using GeneSpring GX software (version 12.6.1). Using Pathway Architect module of GeneSpring GX, the proteins that were found to be overexpressed and hyperphosphorylated in at least four cell lines with a fold change of 1.5 was included for pathway analysis.…”

Section: Bioinformatics Analysismentioning

confidence: 99%

Dysregulation of splicing proteins in head and neck squamous cell carcinoma

Radhakrishnan

Nanjappa

Raja

et al. 2016

Cancer Biology & Therapy

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ABSRTRACTSignaling plays an important role in regulating all cellular pathways. Altered signaling is one of the hallmarks of cancers. Phosphoproteomics enables interrogation of kinase mediated signaling pathways in biological systems. In cancers, this approach can be utilized to identify aberrantly activated pathways that potentially drive proliferation and tumorigenesis. To identify signaling alterations in head and neck squamous cell carcinoma (HNSCC), we carried out proteomic and phosphoproteomic analysis of HNSCC cell lines using a combination of tandem mass tag (TMT) labeling approach and titanium dioxide-based enrichment. We identified 4,920 phosphosites corresponding to 2,212 proteins in six HNSCC cell lines compared to a normal oral cell line. Our data indicated significant enrichment of proteins associated with splicing. We observed hyperphosphorylation of SRSF protein kinase 2 (SRPK2) and its downstream substrates in HNSCC cell lines. SRPK2 is a splicing kinase, known to phosphorylate serine/arginine (SR) rich domain proteins and regulate splicing process in eukaryotes. Although genome-wide studies have reported the contribution of alternative splicing events of several genes in the progression of cancer, the involvement of splicing kinases in HNSCC is not known. In this study, we studied the role of SRPK2 in HNSCC. Inhibition of SRPK2 resulted in significant decrease in colony forming and invasive ability in a panel of HNSCC cell lines. Our results indicate that phosphorylation of SRPK2 plays a crucial role in the regulation of splicing process in HNSCC and that splicing kinases can be developed as a new class of therapeutic target in HNSCC.

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Section: Bioinformatics Analysismentioning

confidence: 99%

Dysregulation of splicing proteins in head and neck squamous cell carcinoma

Radhakrishnan

Nanjappa

Raja

et al. 2016

Cancer Biology & Therapy

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“…For S. cerevisiae , Sce DIP and Sce BGS are two extracted PPI networks from the Database of Interacting Proteins (DIP) [22] and BioGRID [23], respectively. For H. sapiens , Hsa HPRD and Hsa PIPs are corresponding PPI networks derived from Human Protein Reference Database (HPRD) [24] and the PIPs dataset [25]. The details of each PPI network are given in Table 1.…”

Section: Methodsmentioning

confidence: 99%

Joint clustering of protein interaction networks through Markov random walk

Wang

Qian

2014

BMC Systems Biology

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Biological networks obtained by high-throughput profiling or human curation are typically noisy. For functional module identification, single network clustering algorithms may not yield accurate and robust results. In order to borrow information across multiple sources to alleviate such problems due to data quality, we propose a new joint network clustering algorithm ASModel in this paper. We construct an integrated network to combine network topological information based on protein-protein interaction (PPI) datasets and homological information introduced by constituent similarity between proteins across networks. A novel random walk strategy on the integrated network is developed for joint network clustering and an optimization problem is formulated by searching for low conductance sets defined on the derived transition matrix of the random walk, which fuses both topology and homology information. The optimization problem of joint clustering is solved by a derived spectral clustering algorithm. Network clustering using several state-of-the-art algorithms has been implemented to both PPI networks within the same species (two yeast PPI networks and two human PPI networks) and those from different species (a yeast PPI network and a human PPI network). Experimental results demonstrate that ASModel outperforms the existing single network clustering algorithms as well as another recent joint clustering algorithm in terms of complex prediction and Gene Ontology (GO) enrichment analysis.

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“…In another set of analyses, we used the Wiki-Pi database to retrieve NDRG1 protein interactants. Wiki-Pi is a resource that is not manually-curated but allows a large survey of both Biogrid [91] and HPRD [92] databases obtained by high throughput technologies. Wiki-Pi compiles 48419 unique binary biophysical interactions among 10492 human proteins.…”

Section: Meta-analysis Of Mycn Protein Interactantsmentioning

confidence: 99%

A Unique TGFB1-Driven Genomic Program Links Astrocytosis, Low-Grade Inflammation and Partial Demyelination in Periplaques of Spinal Cords from Progressive Multiple Sclerosis Patients

Nataf¹,

Barritault²,

Pays³

2017

Preprint

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Abstract:We previously reported that in multiple sclerosis (MS) patients with a progressive form of the disease, spinal cord periplaques extend distance away from plaque borders and are characterized by the co-occurrence of partial demyelination, astrocytosis and low-grade inflammation. However, transcriptomic analyses comparing periplaques to adjacent normal-appearing white matter (NAWM) areas did not allow providing a comprehensive view of molecular events in astrocytes vs oligodendrocytes. Here, we re-assessed our transcriptomic data with the aim of identifying functionally-relevant co-expression networks that would reflect astrocyte vs oligodendrocyte molecular signatures in periplaques. We identified an astrocytosis-related gene module comprising GFAP, the hub gene CX43/GJA1 and a set of transcripts forming a TGFB/SMAD1/SMAD2 genomic signature. Partial demyelination was characterized by a co-expression network which, besides myelin genes, comprised a highly significant number of translation/elongation-related genes. Interestingly, the main oligodendrocyte-related hub we identified was NDRG1, a gene previously shown to be specifically silenced in the NAWM of MS patients. This result indicated that NDRG1 down-regulation could be an important event in the process of periplaque partial demyelination. To establish a putative link between NDRG1 down-regulation and a cytokine/chemokine signature, we then sought to identify cytokine/chemokine genes whose mRNA levels inversely correlated with those of NDRG1. Following this approach we found 5 candidate immune-related genes whose up-regulation associated with NDRG1 down-regulation: TGFB1, PDGFC, . From these results we propose that in the spinal cord of MS patients with progressive forms of the disease, TGFB1 may Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted:

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Human Protein Reference Database--2009 update

Cited by 2,808 publications

References 24 publications

Dysregulation of splicing proteins in head and neck squamous cell carcinoma

Dysregulation of splicing proteins in head and neck squamous cell carcinoma

Joint clustering of protein interaction networks through Markov random walk

A Unique TGFB1-Driven Genomic Program Links Astrocytosis, Low-Grade Inflammation and Partial Demyelination in Periplaques of Spinal Cords from Progressive Multiple Sclerosis Patients

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