The Experts below are selected from a list of 6768 Experts worldwide ranked by ideXlab platform
Charis Eng - One of the best experts on this subject based on the ideXlab platform.
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Cancer Phenomics: RET and PTEN as illustrative models
Nature Reviews Cancer, 2007Co-Authors: Kevin M. Zbuk, Charis EngAbstract:Cancer Phenomics, the systematic acquisition and objective documentation of host and/or somatic cancer phenotypic data at many levels, is a young field compared with other molecular-based 'omics'. Two relatively advanced phenomic paradigms are associated with phosphatase and tensin homologue ( PTEN ) and rearranged during transfection ( RET ), genes that are associated with cancer predisposition syndromes in addition to developmental disorders. The phenomic characterization of PTEN and RET underscores the importance of incorporating robust Phenomics into the host 'omic' profile, and shows that the evolution of Phenomics will be crucial to the advancement of personalized medicine. Cancer Phenomics refers to the systematic and meticulous collection, objective documentation and cataloguing of phenotypic data at many levels, including clinical, molecular and cellular phenotype. Compared with other genes that predispose to the development of cancer, robust phenomic data exists for rearranged during transfection ( RET ) and phosphatase and tensin homologue ( PTEN ). Germline PTEN and RET mutations predispose to the cancer-associated syndromes Cowden syndrome (CS) and multiple endocrine neoplasia type 2 (MEN 2), respectively. Both genes also predispose to developmental disorders with seemingly disparate phenotypes. CS predisposes to breast, thyroid and endometrial cancer, whereas MEN 2 predisposes to medullary thyroid cancer (MTC), phaeochromocytoma and hyperparathyroidism. Phenomics has shown that germline RET and PTEN mutations are present in a subset of patients with apparently sporadic cancer involving neoplasias that are components of MEN 2 and CS, respectively. Identifying these mutations will have important implications for personalized genetic health care. Meticulous characterization of RET Phenomics at the clinical and biochemical levels has resulted in individualized patient management with respect to cancer surveillance and prophylactic surgery in MEN 2. In addition, Phenomics offers valuable insight into the aetiology of the variable expression of features seen in MEN 2. Through phenomic-based research, the spectrum of phenotypes associated with germline PTEN mutations is continually evolving, and these are collectively termed the PTEN hamartoma tumour syndromes (PHTS). Such research has also led to the continual refinement of the diagnostic criteria for CS. The current opinion is that all patients with PHTS, irrespective of phenotype, follow the cancer surveillance guidelines recommended for CS. These guidelines are updated annually by the US National Comprehensive Cancer Network. Molecular phenomic research has explored new mechanisms of PTEN dysfunction, including splice-site variation and the localization of PTEN to different cellular compartments. Through an understanding of the PTEN–AKT pathway, and its cross-talk with other pathways important in tumorigenesis, the use of targeted therapies seems promising for the treatment of PHTS. However, these agents must be used with caution, as their effects on the development and homeostasis of normal tissue deserves careful consideration. Phenomics is the systematic and meticulous collection, objective documentation and cataloguing of phenotypic data at many levels. This Review describes the possible uses of Phenomics in cancer research, using the examples of RET and PTEN Phenomics.
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Cancer Phenomics: RET and PTEN as illustrative models
Nature reviews. Cancer, 2006Co-Authors: Kevin M. Zbuk, Charis EngAbstract:Phenomics is the systematic and meticulous collection, objective documentation and cataloguing of phenotypic data at many levels. This Review describes the possible uses of Phenomics in cancer research, using the examples of RET and PTEN Phenomics.
Gail E. Gasparich - One of the best experts on this subject based on the ideXlab platform.
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Next-generation Phenomics for the Tree of Life
PLoS currents, 2013Co-Authors: J Gordon Burleigh, Kenzley Alphonse, Andrew J. Alverson, Holly M. Bik, Carrine E. Blank, Andrea L. Cirranello, Hong Cui, Marymegan Daly, Thomas G. Dietterich, Gail E. GasparichAbstract:The phenotype represents a critical interface between the genome and the environment in which organisms live and evolve. Phenotypic characters also are a rich source of biodiversity data for tree building, and they enable scientists to reconstruct the evolutionary history of organisms, including most fossil taxa, for which genetic data are unavailable. Therefore, phenotypic data are necessary for building a comprehensive Tree of Life. In contrast to recent advances in molecular sequencing, which has become faster and cheaper through recent technological advances, phenotypic data collection remains often prohibitively slow and expensive. The next- generation Phenomics project is a collaborative, multidisciplinary effort to leverage advances in image analysis, crowdsourcing, and natural language processing to develop and implement novel approaches for discovering and scoring the phenome, the collection of phentotypic characters for a species. This research represents a new approach to data collection that has the potential to transform phylogenetics research and to enable rapid advances in constructing the Tree of Life. Our goal is to assemble large phenomic datasets built using new methods and to provide the public and scientific community with tools for phenomic data assembly that will enable rapid and automated study of phenotypes across the Tree of Life. Abstract The phenotype represents a critical interface between the genome and the environment in which organisms live and evolve. Phenotypic characters also are a rich source of biodiversity data for tree building, and they enable scientists to reconstruct the evolutionary history of organisms, including most fossil taxa, for which genetic data are unavailable. Therefore, phenotypic data are necessary for building a comprehensive Tree of Life. In contrast to recent advances in molecular sequencing, which has become faster and cheaper through recent technological advances, phenotypic data collection remains often prohibitively slow and expensive. The next- generation Phenomics project is a collaborative, multidisciplinary effort to leverage advances in image analysis, crowdsourcing, and natural language processing to develop and implement novel approaches for discovering and scoring the phenome, the collection of phentotypic characters for a species. This research represents a new approach to data collection that has the potential to transform phylogenetics research and to enable rapid advances in constructing the Tree of Life. Our goal is to assemble large phenomic datasets built using new methods and to provide the public and scientific community with tools for phenomic data assembly that will enable rapid and automated study of phenotypes across the Tree of Life. Abstract The phenotype represents a critical interface between the genome and the environment in which organisms live and evolve. Phenotypic characters also are a rich source of biodiversity data for tree building, and they enable scientists to reconstruct the evolutionary history of organisms, including most fossil taxa, for which genetic data are unavailable. Therefore, phenotypic data are necessary for building a comprehensive Tree of Life. In contrast to recent advances in molecular sequencing, which has become faster and cheaper through recent technological advances, phenotypic data collection remains often prohibitively slow and expensive. The next- generation Phenomics project is a collaborative, multidisciplinary effort to leverage advances in image analysis, crowdsourcing, and natural language processing to develop and implement novel approaches for discovering and scoring the phenome, the collection of phentotypic characters for a species. This research represents a new approach to data collection that has the potential to transform phylogenetics research and to enable rapid advances in constructing the Tree of Life. Our goal is to assemble large phenomic datasets built using new methods and to provide the public and scientific community with tools for phenomic data assembly that will enable rapid and automated study of phenotypes across the Tree of Life.
Kevin M. Zbuk - One of the best experts on this subject based on the ideXlab platform.
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Cancer Phenomics: RET and PTEN as illustrative models
Nature Reviews Cancer, 2007Co-Authors: Kevin M. Zbuk, Charis EngAbstract:Cancer Phenomics, the systematic acquisition and objective documentation of host and/or somatic cancer phenotypic data at many levels, is a young field compared with other molecular-based 'omics'. Two relatively advanced phenomic paradigms are associated with phosphatase and tensin homologue ( PTEN ) and rearranged during transfection ( RET ), genes that are associated with cancer predisposition syndromes in addition to developmental disorders. The phenomic characterization of PTEN and RET underscores the importance of incorporating robust Phenomics into the host 'omic' profile, and shows that the evolution of Phenomics will be crucial to the advancement of personalized medicine. Cancer Phenomics refers to the systematic and meticulous collection, objective documentation and cataloguing of phenotypic data at many levels, including clinical, molecular and cellular phenotype. Compared with other genes that predispose to the development of cancer, robust phenomic data exists for rearranged during transfection ( RET ) and phosphatase and tensin homologue ( PTEN ). Germline PTEN and RET mutations predispose to the cancer-associated syndromes Cowden syndrome (CS) and multiple endocrine neoplasia type 2 (MEN 2), respectively. Both genes also predispose to developmental disorders with seemingly disparate phenotypes. CS predisposes to breast, thyroid and endometrial cancer, whereas MEN 2 predisposes to medullary thyroid cancer (MTC), phaeochromocytoma and hyperparathyroidism. Phenomics has shown that germline RET and PTEN mutations are present in a subset of patients with apparently sporadic cancer involving neoplasias that are components of MEN 2 and CS, respectively. Identifying these mutations will have important implications for personalized genetic health care. Meticulous characterization of RET Phenomics at the clinical and biochemical levels has resulted in individualized patient management with respect to cancer surveillance and prophylactic surgery in MEN 2. In addition, Phenomics offers valuable insight into the aetiology of the variable expression of features seen in MEN 2. Through phenomic-based research, the spectrum of phenotypes associated with germline PTEN mutations is continually evolving, and these are collectively termed the PTEN hamartoma tumour syndromes (PHTS). Such research has also led to the continual refinement of the diagnostic criteria for CS. The current opinion is that all patients with PHTS, irrespective of phenotype, follow the cancer surveillance guidelines recommended for CS. These guidelines are updated annually by the US National Comprehensive Cancer Network. Molecular phenomic research has explored new mechanisms of PTEN dysfunction, including splice-site variation and the localization of PTEN to different cellular compartments. Through an understanding of the PTEN–AKT pathway, and its cross-talk with other pathways important in tumorigenesis, the use of targeted therapies seems promising for the treatment of PHTS. However, these agents must be used with caution, as their effects on the development and homeostasis of normal tissue deserves careful consideration. Phenomics is the systematic and meticulous collection, objective documentation and cataloguing of phenotypic data at many levels. This Review describes the possible uses of Phenomics in cancer research, using the examples of RET and PTEN Phenomics.
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Cancer Phenomics: RET and PTEN as illustrative models
Nature reviews. Cancer, 2006Co-Authors: Kevin M. Zbuk, Charis EngAbstract:Phenomics is the systematic and meticulous collection, objective documentation and cataloguing of phenotypic data at many levels. This Review describes the possible uses of Phenomics in cancer research, using the examples of RET and PTEN Phenomics.
Stig W. Omholt - One of the best experts on this subject based on the ideXlab platform.
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Scan-o-matic: high-resolution microbial Phenomics at a massive scale
2015Co-Authors: Martin Zackrisson, Johan Hallin, Lars-göran Ottosson, Peter Dahl, Esteban Fernandez-parada, Erik Ländström, Luciano Fernandez-ricaud, Petra Kaferle, Andreas Skyman, Stig W. OmholtAbstract:The capacity to map traits over large cohorts of individuals – Phenomics – lags far behind the explosive development in genomics. For microbes the estimation of growth is the key phenotype. We introduce an automated microbial Phenomics framework that delivers accurate and highly resolved growth phenotypes at an unprecedented scale. Advancements were achieved through introduction of transmissive scanning hardware and software technology, frequent acquisition of precise colony population size measurements, extraction of population growth rates from growth curves and removal of spatial bias by reference-surface normalization. Our prototype arrangement automatically records and analyses 100,000 experiments in parallel. We demonstrate the power of the approach by extending and nuancing the known salt defence biology in baker’s yeast. The introduced framework will have a transformative impact by providing high-quality microbial Phenomics data for extensive cohorts of individuals and generating well-populated and standardized Phenomics databases.
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Phenomics: the next challenge.
Nature reviews. Genetics, 2010Co-Authors: David Houle, Diddahally R. Govindaraju, Stig W. OmholtAbstract:A key goal of biology is to understand phenotypic characteristics, such as health, disease and evolutionary fitness. Phenotypic variation is produced through a complex web of interactions between genotype and environment, and such a 'genotype-phenotype' map is inaccessible without the detailed phenotypic data that allow these interactions to be studied. Despite this need, our ability to characterize phenomes - the full set of phenotypes of an individual - lags behind our ability to characterize genomes. Phenomics should be recognized and pursued as an independent discipline to enable the development and adoption of high-throughput and high-dimensional phenotyping.
Gil Alterovitz - One of the best experts on this subject based on the ideXlab platform.
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seeing the forest through the trees uncovering phenomic complexity through interactive network visualization
Journal of the American Medical Informatics Association, 2015Co-Authors: Jeremy L Warner, Joshua C Denny, David A Kreda, Gil AlterovitzAbstract:Our aim was to uncover unrecognized phenomic relationships using force-based network visualization methods, based on observed electronic medical record data. A primary phenotype was defined from actual patient profiles in the Multiparameter Intelligent Monitoring in Intensive Care II database. Network visualizations depicting primary relationships were compared to those incorporating secondary adjacencies. Interactivity was enabled through a phenotype visualization software concept: the Phenomics Advisor. Subendocardial infarction with cardiac arrest was demonstrated as a sample phenotype; there were 332 primarily adjacent diagnoses, with 5423 relationships. Primary network visualization suggested a treatmentrelated complication phenotype and several rare diagnoses; re-clustering by secondary relationships revealed an emergent cluster of smokers with the metabolic syndrome. Network visualization reveals phenotypic patterns that may have remained occult in pairwise correlation analysis. Visualization of complex data, potentially offered as point-of-care tools on mobile devices, may allow clinicians and researchers to quickly generate hypotheses and gain deeper understanding of patient subpopulations.
