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1. Faith in the gap : faith formation in emerging adults involved in a one-year internship programme

Author

White, Peter S.

Subjects
234
Abstract

The research question answered by this thesis is: 'How can a one-year internship programme enable the formation of faith in young adults?' The programme investigated is in the Peterborough Diocese of the Church of England. I lead the internship that facilitates faith formation and vocational discernment. Whilst similar programmes are developing in the Church of England and elsewhere, it is an under-researched area. The research is a qualitative, phenomenological project using a case study with a group of 7 young adults who were participants during one year. Data was collected through semi-structured interviews at the beginning and end of the year, a focus group activity and discussion, and a photography exercise. Engagement with the literature analysed the nature of emerging adulthood, the impact of gap years in other contexts and theological perspectives on the formation of faith. The research aimed to discover the core influences on formation, drawing on practical theology, youth ministry practice and theories of emerging adulthood. The theological concept of habitus is proposed to address some of the challenges of a secular age and prior models of formation that emphasise cognitive processes. Thematic analysis revealed three spheres of influence - relationships, encounter, and narratives of purpose. The concept of vocation is understood as discovering meaningful purpose that develops within the context of covenant community, practices of faith, and learning the story of God that together generate a habitus. The gap year and stage of life offer liminality, an ideal context for change. Faith is described as that which gives meaning and purpose, and formation is the process by which that kind of faith is discovered and shaped. A unique contribution to knowledge is made in drawing together perspectives on faith formation, emerging adulthood, the gap year, and processes of change. Practical recommendations are made to improve my own practice and that of others.

Published
2021

2. CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics

Author

Rappaport Eric F, Xie Hongbo M, Wenocur Adam, D'arcy Monica, O'Hara Ryan, Murphy Kevin, Perin Juan C, Gai Xiaowu, Shaikh Tamim H, and White Peter S

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Recent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opportunity for rapidly assessing research and clinical samples for CNV content, as well as for determining the potential pathogenicity of identified variants. However, few informatics tools for accurate and efficient CNV detection and assessment currently exist. Results We developed a suite of software tools and resources (CNV Workshop) for automated, genome-wide CNV detection from a variety of SNP array platforms. CNV Workshop includes three major components: detection, annotation, and presentation of structural variants from genome array data. CNV detection utilizes a robust and genotype-specific extension of the Circular Binary Segmentation algorithm, and the use of additional detection algorithms is supported. Predicted CNVs are captured in a MySQL database that supports cohort-based projects and incorporates a secure user authentication layer and user/admin roles. To assist with determination of pathogenicity, detected CNVs are also annotated automatically for gene content, known disease loci, and gene-based literature references. Results are easily queried, sorted, filtered, and visualized via a web-based presentation layer that includes a GBrowse-based graphical representation of CNV content and relevant public data, integration with the UCSC Genome Browser, and tabular displays of genomic attributes for each CNV. Conclusions To our knowledge, CNV Workshop represents the first cohesive and convenient platform for detection, annotation, and assessment of the biological and clinical significance of structural variants. CNV Workshop has been successfully utilized for assessment of genomic variation in healthy individuals and disease cohorts and is an ideal platform for coordinating multiple associated projects. Availability and Implementation Available on the web at: http://sourceforge.net/projects/cnv

Published
2010
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3. Automated recognition of malignancy mentions in biomedical literature

Author

Liberman Mark Y, Carroll Steven, Mandel Mark A, Lerman Kevin, McDonald Ryan T, Jin Yang, Pereira Fernando C, Winters Raymond S, and White Peter S

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background The rapid proliferation of biomedical text makes it increasingly difficult for researchers to identify, synthesize, and utilize developed knowledge in their fields of interest. Automated information extraction procedures can assist in the acquisition and management of this knowledge. Previous efforts in biomedical text mining have focused primarily upon named entity recognition of well-defined molecular objects such as genes, but less work has been performed to identify disease-related objects and concepts. Furthermore, promise has been tempered by an inability to efficiently scale approaches in ways that minimize manual efforts and still perform with high accuracy. Here, we have applied a machine-learning approach previously successful for identifying molecular entities to a disease concept to determine if the underlying probabilistic model effectively generalizes to unrelated concepts with minimal manual intervention for model retraining. Results We developed a named entity recognizer (MTag), an entity tagger for recognizing clinical descriptions of malignancy presented in text. The application uses the machine-learning technique Conditional Random Fields with additional domain-specific features. MTag was tested with 1,010 training and 432 evaluation documents pertaining to cancer genomics. Overall, our experiments resulted in 0.85 precision, 0.83 recall, and 0.84 F-measure on the evaluation set. Compared with a baseline system using string matching of text with a neoplasm term list, MTag performed with a much higher recall rate (92.1% vs. 42.1% recall) and demonstrated the ability to learn new patterns. Application of MTag to all MEDLINE abstracts yielded the identification of 580,002 unique and 9,153,340 overall mentions of malignancy. Significantly, addition of an extensive lexicon of malignancy mentions as a feature set for extraction had minimal impact in performance. Conclusion Together, these results suggest that the identification of disparate biomedical entity classes in free text may be achievable with high accuracy and only moderate additional effort for each new application domain.

Published
2006
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4. Neptune: an environment for the delivery of genomic medicine

Author

Eric, Venner, Yi, Victoria, Murdock, David, Kalla, Sara E., Wu, Tsung-Jung, Sabo, Aniko, Li, Shoudong, Meng, Qingchang, Tian, Xia, Murugan, Mullai, Cohen, Michelle, Kovar, Christie, Wei, Wei-Qi, Chung, Wendy K., Weng, Chunhua, Wiesner, Georgia L., Jarvik, Gail P., Muzny, Donna, Gibbs, Richard A., Abrams, Debra, Adunyah, Samuel E., Albertson-Junkans, Ladia, Almoguera, Berta, Ames, Darren C., Appelbaum, Paul, Aronson, Samuel, Aufox, Sharon, Babb, Lawrence J., Balasubramanian, Adithya, Bangash, Hana, Basford, Melissa, Bastarache, Lisa, Baxter, Samantha, Behr, Meckenzie, Benoit, Barbara, Bhoj, Elizabeth, Bielinski, Suzette J., Bland, Harris T., Blout, Carrie, Borthwick, Kenneth, Bottinger, Erwin P., Bowser, Mark, Brand, Harrison, Brilliant, Murray, Brodeur, Wendy, Caraballo, Pedro, Carrell, David, Carroll, Andrew, Castillo, Lisa, Castro, Victor, Chandanavelli, Gauthami, Chiang, Theodore, Chisholm, Rex L., Christensen, Kurt D., Chung, Wendy, Chute, Christopher G., City, Brittany, Cobb, Beth L., Connolly, John J., Crane, Paul, Crew, Katherine, Crosslin, David R., Dayal, Jyoti, De Andrade, Mariza, De la Cruz, Jessica, Denny, Josh C., Denson, Shawn, DeSmet, Tim, Dikilitas, Ozan, Dinsmore, Michael J., Dodge, Sheila, Dunlea, Phil, Edwards, Todd L., Eng, Christine M., Fasel, David, Fedotov, Alex, Feng, Qiping, Fleharty, Mark, Foster, Andrea, Freimuth, Robert, Friedrich, Christopher, Fullerton, Stephanie M., Funke, Birgit, Gabriel, Stacey, Gainer, Vivian, Gharavi, Ali, Glazer, Andrew M., Glessner, Joseph T., Goehringer, Jessica, Gordon, Adam S., Graham, Chet, Green, Robert C., Gundelach, Justin H., Hain, Heather S., Hakonarson, Hakon, Harden, Maegan V., Harley, John, Harr, Margaret, Hartzler, Andrea, Hayes, M. Geoffrey, Hebbring, Scott, Henrikson, Nora, Hershey, Andrew, Hoell, Christin, Holm, Ingrid, Howell, Kayla M., Hripcsak, George, Hu, Jianhong, Hynes, Elizabeth Duffy, Jayaseelan, Joy C., Jiang, Yunyun, Joo, Yoonjung Yoonie, Jose, Sheethal, Josyula, Navya Shilpa, Justice, Anne E., Kalra, Divya, Karlson, Elizabeth W., Keating, Brendan J., Kelly, Melissa A., Kenny, Eimear E., Key, Dustin, Kiryluk, Krzysztof, Kitchner, Terrie, Klanderman, Barbara, Klee, Eric, Kochan, David C., Korchina, Viktoriya, Kottyan, Leah, Kudalkar, Emily, Rahm, Alanna Kulchak, Kullo, Iftikhar J., Lammers, Philip, Larson, Eric B., Lebo, Matthew S., Leduc, Magalie, Lee, Ming Ta (Michael), Lennon, Niall J., Leppig, Kathleen A., Leslie, Nancy D., Li, Rongling, Liang, Wayne H., Lin, Chiao-Feng, Linder, Jodell E., Lindor, Noralane M., Lingren, Todd, Linneman, James G., Liu, Cong, Liu, Wen, Liu, Xiuping, Lynch, John, Lyon, Hayley, Macbeth, Alyssa, Mahadeshwar, Harshad, Mahanta, Lisa, Malin, Bradley, Manolio, Teri, Marasa, Maddalena, Marsolo, Keith, McGowan, Michelle L., McNally, Elizabeth, Meldrim, Jim, Mentch, Frank, Rasouly, Hila Milo, Mosley, Jonathan, Mukherjee, Shubhabrata, Mullen, Thomas E., Muniz, Jesse, Murdock, David R., Murphy, Shawn, Myers, Melanie F., Namjou, Bahram, Ni, Yizhao, Onofrio, Robert C., Obeng, Aniwaa Owusu, Person, Thomas N., Peterson, Josh F., Petukhova, Lynn, Pisieczko, Cassandra J., Pratap, Siddharth, Prows, Cynthia A., Puckelwartz, Megan J., Raj, Ritika, Ralston, James D., Ramaprasan, Arvind, Ramirez, Andrea, Rasmussen, Luke, Rasmussen-Torvik, Laura, Raychaudhuri, Soumya, Rehm, Heidi L., Ritchie, Marylyn D., Rives, Catherine, Riza, Beenish, Roden, Dan M., Rosenthal, Elisabeth A., Santani, Avni, Dan, Schaid, Scherer, Steven, Scott, Stuart, Scrol, Aaron, Sengupta, Soumitra, Shang, Ning, Sharma, Himanshu, Sharp, Richard R., Singh, Rajbir, Sleiman, Patrick M.A., Slowik, Kara, Smith, Joshua C., Smith, Maureen E., Smoot, Duane T., Smoller, Jordan W., Sohn, Sunghwan, Stanaway, Ian B., Starren, Justin, Stroud, Mary, Su, Jessica, Taylor, Casey Overby, Tolwinski, Kasia, Van Driest, Sara L., Vargas, Sean M., Varugheese, Matthew, Veenstra, David, Venner, Eric, Verbitsky, Miguel, Vicente, Gina, Wagner, Michael, Walker, Kimberly, Walunas, Theresa, Wang, Liwen, Wang, Qiaoyan, Weiss, Scott T., Wells, Quinn S., White, Peter S., Wiley, Ken L., Jr, Williams, Janet L., Williams, Marc S., Wilson, Michael W., Witkowski, Leora, Woods, Laura Allison, Woolf, Betty, Wynn, Julia, Yang, Yaping, Zhang, Ge, Zhang, Lan, and Zouk, Hana

Published
2021
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7. Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network

Author

Zouk, Hana, Venner, Eric, Lennon, Niall J., Muzny, Donna M., Abrams, Debra, Adunyah, Samuel, Albertson-Junkans, Ladia, Ames, Darren C., Appelbaum, Paul, Aronson, Samuel, Aufox, Sharon, Babb, Lawrence J., Balasubramanian, Adithya, Bangash, Hana, Basford, Melissa, Bastarache, Lisa, Baxter, Samantha, Behr, Meckenzie, Benoit, Barbara, Bhoj, Elizabeth, Bielinski, Suzette J., Bland, Sarah T., Blout, Carrie, Borthwick, Kenneth, Bottinger, Erwin P., Bowser, Mark, Brand, Harrison, Brilliant, Murray, Brodeur, Wendy, Caraballo, Pedro, Carrell, David, Carroll, Andrew, Almoguera, Berta, Castillo, Lisa, Castro, Victor, Chandanavelli, Gauthami, Chiang, Theodore, Chisholm, Rex L., Christensen, Kurt D., Chung, Wendy, Chute, Christopher G., City, Brittany, Cobb, Beth L., Connolly, John J., Crane, Paul, Crew, Katherine, Crosslin, David, De Andrade, Mariza, De la Cruz, Jessica, Denson, Shawn, Denny, Josh, DeSmet, Tim, Dikilitas, Ozan, Friedrich, Christopher, Fullerton, Stephanie M., Funke, Birgit, Gabriel, Stacey, Gainer, Vivian, Gharavi, Ali, Glazer, Andrew M., Glessner, Joseph T., Goehringer, Jessica, Gordon, Adam S., Graham, Chet, Green, Robert C., Gundelach, Justin H., Dayal, Jyoti, Hain, Heather S., Hakonarson, Hakon, Harden, Maegan V., Harley, John, Harr, Margaret, Hartzler, Andrea, Hayes, M. Geoffrey, Hebbring, Scott, Henrikson, Nora, Hershey, Andrew, Hoell, Christin, Holm, Ingrid, Howell, Kayla M., Hripcsak, George, Hu, Jianhong, Jarvik, Gail P., Jayaseelan, Joy C., Jiang, Yunyun, Joo, Yoonjung Yoonie, Jose, Sheethal, Josyula, Navya Shilpa, Justice, Anne E., Kalla, Sara E., Kalra, Divya, Karlson, Elizabeth, Kelly, Melissa A., Keating, Brendan J., Kenny, Eimear E., Key, Dustin, Kiryluk, Krzysztof, Kitchner, Terrie, Klanderman, Barbara, Klee, Eric, Kochan, David C., Korchina, Viktoriya, Kottyan, Leah, Kovar, Christie, Kudalkar, Emily, Kullo, Iftikhar J., Lammers, Philip, Larson, Eric B., Lebo, Matthew S., Leduc, Magalie, Lee, Ming Ta (Michael), Leppig, Kathleen A., Leslie, Nancy D., Li, Rongling, Liang, Wayne H., Lin, Chiao-Feng, Linder, Jodell, Lindor, Noralane M., Lingren, Todd, Linneman, James G., Liu, Cong, Liu, Wen, Liu, Xiuping, Lynch, John, Lyon, Hayley, Macbeth, Alyssa, Mahadeshwar, Harshad, Mahanta, Lisa, Malin, Brad, Manolio, Teri, Marasa, Maddalena, Marsolo, Keith, Dinsmore, Michael J., Dodge, Sheila, Hynes, Elizabeth Duffy, Dunlea, Phil, Edwards, Todd L., Eng, Christine M., Fasel, David, Fedotov, Alex, Feng, Qiping, Fleharty, Mark, Foster, Andrea, Freimuth, Robert, McGowan, Michelle L., McNally, Elizabeth, Meldrim, Jim, Mentch, Frank, Mosley, Jonathan, Mukherjee, Shubhabrata, Mullen, Thomas E., Muniz, Jesse, Murdock, David R., Murphy, Shawn, Murugan, Mullai, Myers, Melanie F., Namjou, Bahram, Ni, Yizhao, Obeng, Aniwaa Owusu, Onofrio, Robert C., Taylor, Casey Overby, Person, Thomas N., Peterson, Josh F., Petukhova, Lynn, Pisieczko, Cassandra J., Pratap, Siddharth, Prows, Cynthia A., Puckelwartz, Megan J., Rahm, Alanna Kulchak, Raj, Ritika, Ralston, James D., Ramaprasan, Arvind, Ramirez, Andrea, Rasmussen, Luke, Rasmussen-Torvik, Laura, Rasouly, Hila Milo, Raychaudhuri, Soumya, Ritchie, Marylyn D., Rives, Catherine, Riza, Beenish, Roden, Dan, Rosenthal, Elisabeth A., Santani, Avni, Schaid, Dan, Scherer, Steven, Scott, Stuart, Scrol, Aaron, Sengupta, Soumitra, Shang, Ning, Sharma, Himanshu, Sharp, Richard R., Singh, Rajbir, Sleiman, Patrick M.A., Slowik, Kara, Smith, Joshua C., Smith, Maureen E., Smoller, Jordan W., Sohn, Sunghwan, Stanaway, Ian B., Starren, Justin, Stroud, Mary, Su, Jessica, Tolwinski, Kasia, Van Driest, Sara L., Vargas, Sean M., Varugheese, Matthew, Veenstra, David, Verbitsky, Miguel, Vicente, Gina, Wagner, Michael, Walker, Kimberly, Walunas, Theresa, Wang, Liwen, Wang, Qiaoyan, Wei, Wei-Qi, Weiss, Scott T., Wiesner, Georgia L., Wells, Quinn, Weng, Chunhua, White, Peter S., Wiley, Ken L., Jr., Williams, Janet L., Williams, Marc S., Wilson, Michael W., Witkowski, Leora, Woods, Laura Allison, Woolf, Betty, Wu, Tsung-Jung, Wynn, Julia, Yang, Yaping, Yi, Victoria, Zhang, Ge, Zhang, Lan, Rehm, Heidi L., and Gibbs, Richard A.

Published
2019
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8. Increased Frequency of De Novo Copy Number Variants in Congenital Heart Disease by Integrative Analysis of Single Nucleotide Polymorphism Array and Exome Sequence Data

Author

Glessner, Joseph T, Bick, Alexander G, Ito, Kaoru, Homsy, Jason, Rodriguez-Murillo, Laura, Fromer, Menachem, Mazaika, Erica, Vardarajan, Badri, Italia, Michael, Leipzig, Jeremy, DePalma, Steven R, Golhar, Ryan, Sanders, Stephan J, Yamrom, Boris, Ronemus, Michael, Iossifov, Ivan, Willsey, A Jeremy, State, Matthew W, Kaltman, Jonathan R, White, Peter S, Shen, Yufeng, Warburton, Dorothy, Brueckner, Martina, Seidman, Christine, Goldmuntz, Elizabeth, Gelb, Bruce D, Lifton, Richard, Seidman, Jonathan, Hakonarson, Hakon, and Chung, Wendy K

Subjects
Human Genome, Pediatric, Congenital Structural Anomalies, Genetics, Cardiovascular, Heart Disease, Aetiology, 2.1 Biological and endogenous factors, Case-Control Studies, Cohort Studies, DNA Copy Number Variations, Exome, Gene Frequency, Gene Regulatory Networks, Heart Defects, Congenital, Humans, Molecular Sequence Data, Polymorphism, Single Nucleotide, DNA copy number variations, genomics, microarray analysis, polymorphism, single nucleotide, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

RationaleCongenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown pathogenesis.ObjectiveTo determine the contribution of de novo copy number variants (CNVs) in the pathogenesis of sporadic CHD.Methods and resultsWe studied 538 CHD trios using genome-wide dense single nucleotide polymorphism arrays and whole exome sequencing. Results were experimentally validated using digital droplet polymerase chain reaction. We compared validated CNVs in CHD cases with CNVs in 1301 healthy control trios. The 2 complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either single nucleotide polymorphism array (P=7×10(-5); odds ratio, 4.6) or whole exome sequencing data (P=6×10(-4); odds ratio, 3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (P=0.02; odds ratio, 2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in whole exome sequencing and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q subtelomeric deletions.ConclusionsWe demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD.

Published
2014

40. Microclimate moderates plant responses to macroclimate warming

Author

De Frenne, Pieter, Rodríguez-Sánchez, Francisco, Coomes, David Anthony, Baeten, Lander, Verstraeten, Gorik, Vellend, Mark, Bernhardt-Römermann, Markus, Brown, Carissa D., Brunet, Jörg, Cornelis, Johnny, Decocq, Guillaume M., Dierschke, Hartmut, Eriksson, Ove, Gilliam, Frank S., Hédl, Radim, Heinken, Thilo, Hermy, Martin, Hommel, Patrick, Jenkins, Michael A., Kelly, Daniel L., Kirby, Keith J., Mitchell, Fraser J. G., Naaf, Tobias, Newman, Miles, Peterken, George, Patřík, Petr, Schultz, Jan, Sonnier, Grégory, Van Calster, Hans, Waller, Donald M., Walther, Gian-Reto, White, Peter S., Woods, Kerry D., Wulf, Monika, Graae, Bente Jessen, and Verheyen, Kris

Published
2013

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