SPIRE: Systematic protein investigative research environment

Kolker, Eugene; Higdon, Roger; Welch, Dean; Bauman, Andrew T.; Stewart, Elizabeth; Haynes, Winston; Broomall, William; Kolker, Natali

doi:10.1016/j.jprot.2011.05.009

Cited by 28 publications

(35 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Alternatively, clustering can be applied jointly to different sets; indeed, several approaches have been developed to do that (Shen et al, 2010). All of these approaches will benefit for consistently processed, normalized, and analyzed expression data (Holzman and Kolker, 2004;Kolker et al, 2011).…”

Section: Classifying Patients Into Subtypesmentioning

confidence: 99%

The Promise of Multi-Omics and Clinical Data Integration to Identify and Target Personalized Healthcare Approaches in Autism Spectrum Disorders

Higdon

Earl

Stanberry

et al. 2015

OMICS: A Journal of Integrative Biology

Self Cite

View full text Add to dashboard Cite

Complex diseases are caused by a combination of genetic and environmental factors, creating a difficult challenge for diagnosis and defining subtypes. This review article describes how distinct disease subtypes can be identified through integration and analysis of clinical and multi-omics data. A broad shift toward molecular subtyping of disease using genetic and omics data has yielded successful results in cancer and other complex diseases. To determine molecular subtypes, patients are first classified by applying clustering methods to different types of omics data, then these results are integrated with clinical data to characterize distinct disease subtypes. An example of this molecular-data-first approach is in research on Autism Spectrum Disorder (ASD), a spectrum of social communication disorders marked by tremendous etiological and phenotypic heterogeneity. In the case of ASD, omics data such as exome sequences and gene and protein expression data are combined with clinical data such as psychometric testing and imaging to enable subtype identification. Novel ASD subtypes have been proposed, such as CHD8, using this molecular subtyping approach. Broader use of molecular subtyping in complex disease research is impeded by data heterogeneity, diversity of standards, and ineffective analysis tools. The future of molecular subtyping for ASD and other complex diseases calls for an integrated resource to identify disease mechanisms, classify new patients, and inform effective treatment options. This in turn will empower and accelerate precision medicine and personalized healthcare.

show abstract

Section: Classifying Patients Into Subtypesmentioning

confidence: 99%

The Promise of Multi-Omics and Clinical Data Integration to Identify and Target Personalized Healthcare Approaches in Autism Spectrum Disorders

Higdon

Earl

Stanberry

et al. 2015

OMICS: A Journal of Integrative Biology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Методические особенности количественной масс-спектрометрии подробно рассмотрены в ряде обзорных статей [24][25][26][27][28].…”

Section: транскриптомные и протеомные методы -методологическая платфоunclassified

Transcriptomics and proteomics in studies of induced differentiation of leukemia cells

Novikova

Zgoda

2015

BIOMED KHIM

View full text Add to dashboard Cite

show abstract

“…Northern analysis of NCBI's uniGene dataset was also extracted (21). Moreover, protein expression of HRH1 was obtained from SPIRE (28) and MOPED (29).…”

Section: Identificationmentioning

confidence: 99%

Integrative genomic analyses of the histamine H1 receptor and its role in cancer prediction

Wang

Wei

Shi

et al. 2014

International Journal of Molecular Medicine

View full text Add to dashboard Cite

Abstract. The human histamine receptor H1 (HRH1) gene is located on chromosome 3p25 and encodes for a 487 amino acid G protein-coupled receptor (GPCR) with a long third intracellular loop (IL3). The HRH1 predominantly couples to Gα q/11 proteins, leading to the activation of phospholipase C (PLC) and subsequent release of the second messengers inositol trisphosphate (IP 3 ) and diacylglycerol (DAG) followed by the activation of PKC and the release of [Ca 2+ ] i . In the present study, we identified HRH1 genes from 14 vertebrate genomes and found that HRH1 exists in all types of vertebrates including fish, amphibians, birds and mammals. We identified 88 SNPs including 4 available alleles disrupting an existing exonic splicing enhancer and 84 SNPs causing missense mutation, which may impact the effect of histamine on the HRH1 protein. We found that the human HRH1 gene was expressed in many tissues or organs, and predominant expression of HRH1 was shown in the bone marrow, whole blood, lymph node, thymus, brain, cerebellum, retina, spinal cord, heart, smooth muscle, skeletal muscle, small intestine, colon, adipocytes, kidney, liver, lung, pancreas, thyroid salivary gland, skin, ovary, uterus, placenta, prostate and testis. When searched in the PrognoScan database, human HRH1 was also found to be expressed in bladder cancer, blood cancer, brain cancer, breast cancer, colorectal cancer, eye cancer, head and neck cancer, lung cancer, ovarian cancer, skin cancer and soft tissue cancer tissues. The relationship between the expression of HRH1 and prognosis was found to vary in different types of cancers, even in the same cancer from different databases. This implies that the function of HRH1 in these tumors may be multidimensional. GR, STAT5A and c-Myb regulatory transcription factor binding sites were identified in the HRH1 gene upstream (promoter) region, which may be involved in the effect of HRH1 in tumors.

show abstract

SPIRE: Systematic protein investigative research environment

Cited by 28 publications

References 23 publications

The Promise of Multi-Omics and Clinical Data Integration to Identify and Target Personalized Healthcare Approaches in Autism Spectrum Disorders

The Promise of Multi-Omics and Clinical Data Integration to Identify and Target Personalized Healthcare Approaches in Autism Spectrum Disorders

Transcriptomics and proteomics in studies of induced differentiation of leukemia cells

Integrative genomic analyses of the histamine H1 receptor and its role in cancer prediction

Contact Info

Product

Resources

About