HAPPI: an online database of comprehensive human annotated and predicted protein interactions

Chen, Jake Y.; Mamidipalli, SudhaRani; Huan, Tianxiao

doi:10.1186/1471-2164-10-s1-s16

Cited by 148 publications

(98 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3 and supplemental Fig. S3B) based on their known EGFR interactions as listed in the databases HAPPI (50) or HPRD (51), and/or known to be involved in endocytosis/trafficking, or associated with the processes of phosphorylation or ubiquitination. EGFR amount was used to normalize the quantification of associated proteins (see arrow in Fig.…”

Section: Effect Of Temperature Ligand and Stress On Egfr Phosphorylmentioning

confidence: 99%

Proteomic Analysis of the Epidermal Growth Factor Receptor (EGFR) Interactome and Post-translational Modifications Associated with Receptor Endocytosis in Response to EGF and Stress

Tong¹,

Taylor²,

Moran³

2014

Molecular & Cellular Proteomics

107

View full text Add to dashboard Cite

Aberrant expression, activation, and stabilization of epidermal growth factor receptor (EGFR) are causally associated with several human cancers. Post-translational modifications and protein-protein interactions directly modulate the signaling and trafficking of the EGFR. Activated EGFR is internalized by endocytosis and then either recycled back to the cell surface or degraded in the lysosome. EGFR internalization and recycling also occur in response to stresses that activate p38 MAP kinase. Mass spectrometry was applied to comprehensively analyze the phosphorylation, ubiquitination, and protein-protein interactions of wild type and endocytosis-defective EGFR variants before and after internalization in response to EGF ligand and stress. Prior to internalization, EGF-stimulated EGFR accumulated ubiquitin at 7 K residues and phosphorylation at 7 Y sites and at S 1104 . Following internalization, these modifications diminished and there was an accumulation of S/T phosphorylations. EGFR internalization and many but not all of the EGF-induced S/T phosphorylations were also stimulated by anisomycin-induced cell stress, which was not associated with receptor ubiquitination or elevated Y phosphorylation. EGFR protein interactions were dramatically modulated by ligand, internalization, and stress. In response to EGF, different E3 ubiquitin ligases became maximally associated with EGFR before (CBL, HUWE1, and UBR4) or after (ITCH) internalization, whereas CBLB was distinctively most highly EGFR associated following anisomycin treatment. Adaptin subunits of AP-1 and AP-2 clathrin adaptor complexes also became EGFR associated in response to EGF and anisomycin stress. Mutations preventing EGFR phosphorylation at Y 998 or in the S 1039 region abolished or greatly reduced EGFR interactions with AP-2 and AP-1, and impaired receptor trafficking. These results provide new insight into spatial, temporal, and mechanistic aspects of EGFR regulation. Molecular & Cellular

show abstract

Section: Effect Of Temperature Ligand and Stress On Egfr Phosphorylmentioning

confidence: 99%

Proteomic Analysis of the Epidermal Growth Factor Receptor (EGFR) Interactome and Post-translational Modifications Associated with Receptor Endocytosis in Response to EGF and Stress

Tong¹,

Taylor²,

Moran³

2014

Molecular & Cellular Proteomics

107

View full text Add to dashboard Cite

show abstract

“…Inconsistent data quality has previously been identified as an impediment to the construction of biological networks [20,21] and clinical databases [22,23]. One of the major challenges to studying human diseases computationally is the development of vocabularies and ontologies that realistically reflect the complex inter-relationships among phenotypes.…”

Section: Discussionmentioning

confidence: 99%

Dynamic, Multi-Level Network Models of Clinical Trials

Sorani¹,

Manley²,

Hemphill³

et al. 2010

Biocomputing 2011

View full text Add to dashboard Cite

While networks models have often been applied to complex biological systems, they are increasingly being implemented to investigate clinical questions. Clinical trials have been studied extensively by traditional statistical methods but never, to our knowledge, using networks. We obtained data for 6,847 clinical trials from five "Nervous System Diseases" (NSD) and five "Behaviors and Mental Disorders" (BMD) from the clinicaltrials.gov registry. We constructed networks of diseases and interventions for visualization and analysis using Cytoscape software. To standardize nomenclature and enable multi-level annotation, we used MeSH and UMLS terms. We then constructed separate BMD and NSD networks to study dynamics over time. To assess how topology features related to clinical significance, we constructed a sub-network of Multiple Sclerosis and Alzheimer's trials and identified which trials had been published in high-profile medical journals. We found that the BMD network has evolved into a large, decentralized topology and does not distinctly reflect the five diseases by which it was defined, while the NSD network does, though other diseases and sub-phenotypes have emerged as areas of research. We also found that high-profile trials have distinctive network characteristics. Future work is needed to address mathematical questions such as scale-dependence of network features, clinical questions such as trial design optimization, and methodological questions such as data quality improvement.

show abstract

“…Though numerous human PPI databases were found at that time yet defining all features of data was poor. The author named this data management system as Human Annotated and Predicted Protein Interaction (HAPPI) [21] database that is positioned at extraction and integration of new proteins interaction databases, which consists of BIND, STRING HPRD, MINT, and OPHID by means of database assimilation procedures.…”

Section: Related Workmentioning

confidence: 99%

A Novel Big Data Storage Model for Protein-Protein Interaction and Gene-Protein Associations

Sarwar¹,

Yaseen²,

Ferzund³

et al. 2017

ijacsa

View full text Add to dashboard Cite

show abstract

HAPPI: an online database of comprehensive human annotated and predicted protein interactions

Cited by 148 publications

References 54 publications

Proteomic Analysis of the Epidermal Growth Factor Receptor (EGFR) Interactome and Post-translational Modifications Associated with Receptor Endocytosis in Response to EGF and Stress

Proteomic Analysis of the Epidermal Growth Factor Receptor (EGFR) Interactome and Post-translational Modifications Associated with Receptor Endocytosis in Response to EGF and Stress

Dynamic, Multi-Level Network Models of Clinical Trials

A Novel Big Data Storage Model for Protein-Protein Interaction and Gene-Protein Associations

Contact Info

Product

Resources

About