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David C. Page

Bio: David C. Page is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Y chromosome & X chromosome. The author has an hindex of 110, co-authored 509 publications receiving 44119 citations. Previous affiliations of David C. Page include Hennepin County Medical Center & University of California, Los Angeles.


Papers
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Journal ArticleDOI
19 Jun 2003-Nature
TL;DR: The male-specific region of the Y chromosome, the MSY, differentiates the sexes and comprises 95% of the chromosome's length, and is a mosaic of heterochromatic sequences and three classes of euchromatics sequences: X-transposed, X-degenerate and ampliconic.
Abstract: The male-specific region of the Y chromosome, the MSY, differentiates the sexes and comprises 95% of the chromosome's length. Here, we report that the MSY is a mosaic of heterochromatic sequences and three classes of euchromatic sequences: X-transposed, X-degenerate and ampliconic. These classes contain all 156 known transcription units, which include 78 protein-coding genes that collectively encode 27 distinct proteins. The X-transposed sequences exhibit 99% identity to the X chromosome. The X-degenerate sequences are remnants of ancient autosomes from which the modern X and Y chromosomes evolved. The ampliconic class includes large regions (about 30% of the MSY euchromatin) where sequence pairs show greater than 99.9% identity, which is maintained by frequent gene conversion (non-reciprocal transfer). The most prominent features here are eight massive palindromes, at least six of which contain testis genes.

2,022 citations

Journal ArticleDOI
TL;DR: The use of a pharmacogenetic algorithm for estimating the appropriate initial dose of warfarin produces recommendations that are significantly closer to the required stable therapeutic dose than those derived from a clinical algorithm or a fixed-dose approach.
Abstract: Warfarin is one of the most widely used anticoagulants in the world. Treatment is complicated by a large inter-individual variation in the dose needed to reach adequate levels of anticoagulation i.e. INR 2.0 – 3.0. The objective of this thesis was to evaluate which factors, mainly genetic but also non-genetic, that affect the response to warfarin in terms of required maintenance dose, efficacy and safety with special focus on warfarin dose prediction.Through candidate gene and genome-wide studies, we have shown that the genes CYP2C9 and VKORC1 are the major determinants of warfarin maintenance dose. By combining the SNPs CYP2C9 *2, CYP2C9 *3 and VKORC1 rs9923231 with the clinical factors age, height, weight, ethnicity, amiodarone and use of inducers (carbamazepine, phenytoin or rifampicin) into a prediction model (the IWPC model) we can explain 43 % to 51 % of the variation in warfarin maintenance dose. Patients requiring doses < 29 mg/week and doses ≥ 49 mg/week benefitted the most from pharmacogenetic dosing. Further, we have shown that the difference across ethnicities in percent variance explained by VKORC1 was largely accounted for by the allele frequency of rs9923231. Other novel genes affecting maintenance dose (NEDD4 and DDHD1), as well as the replicated CYP4F2 gene, have small effects on dose predictions and are not likely to be cost-effective, unless inexpensive genotyping is available.Three types of prediction models for warfarin dosing exist: maintenance dose models, loading dose models and dose revision models. The combination of these three models is currently being used in the warfarin treatment arm of the European Pharmacogenetics of Anticoagulant Therapy (EU-PACT) study. Other clinical trials aiming to prove the clinical validity and utility of pharmacogenetic dosing are also underway.The future of pharmacogenetic warfarin dosing relies on results from these ongoing studies, the availability of inexpensive genotyping and the cost-effectiveness of pharmacogenetic driven warfarin dosing compared with new oral anticoagulant drugs.

1,504 citations

Journal ArticleDOI
TL;DR: The region contains a single–copy gene, DAZ (Deleted in AZoospermia), which is transcribed in the adult testis and appears to encode an RNA binding protein, and the possibility that DAZ is AZF should now be explored.
Abstract: We have detected deletions of portions of the Y chromosome long arm in 12 of 89 men with azoospermia (no sperm in semen). No Y deletions were detected in their male relatives or in 90 other fertile males. The 12 deletions overlap, defining a region likely to contain one or more genes required for spermatogenesis (the Azoospermia Factor, AZF). Deletion of the AZF region is associated with highly variable testicular defects, ranging from complete absence of germ cells to spermatogenic arrest with occasional production of condensed spermatids. We find no evidence of YRRM genes, recently proposed as AZF candidates, in the AZF region. The region contains a single–copy gene, DAZ (Deleted in AZoospermia), which is transcribed in the adult testis and appears to encode an RNA binding protein. The possibility that DAZ is AZF should now be explored.

1,133 citations

Journal ArticleDOI
Gregory D. Schuler1, Mark S. Boguski1, Elizabeth A. Stewart2, Lincoln Stein3, Gabor Gyapay, Kate Rice4, Robert E. White5, P. Rodriguez-Tomé6, Amita Aggarwal2, Eva Bajorek2, S. Bentolila, B. B. Birren3, Adam Butler4, Andrew B. Castle3, N. Chiannilkulchai, Angela M. Chu2, C M Clee4, Sid Cowles2, P. J. R. Day5, T. Dibling4, N. Drouot, Ian Dunham4, Simone Duprat, C. East4, C A Edwards4, Jun Fan2, Nicole Y. Fang7, Cécile Fizames, Christine Garrett4, L. Green4, David Hadley2, Midori A. Harris2, Paul Harrison4, Shannon T. Brady2, Andrew A. Hicks4, E. Holloway4, L. Hui3, S. Hussain2, C. Louis-Dit-Sully5, J. Ma3, A. MacGilvery4, Christopher Mader2, A. Maratukulam2, Tara C. Matise8, K. B. McKusick2, Jean Morissette9, Andrew J. Mungall4, Delphine Muselet, H. C. Nusbaum3, David C. Page3, Ammon B. Peck4, Shanti M. Perkins2, Mark Piercy2, Fawn Qin2, John Quackenbush2, S A Ranby4, Tim Reif2, Steve Rozen3, C. Sanders2, X. She2, James Silva3, Donna K. Slonim3, Carol Soderlund4, W.-L. Sun2, P. Tabar2, T. Thangarajah5, Nathalie Vega-Czarny, Douglas Vollrath2, S. Voyticky2, T. E. Wilmer4, Xiao-Yu Wu3, Mark Raymond Adams10, Charles Auffray11, Nicole A.R. Walter12, Rhonda Brandon10, Anindya Dehejia1, Peter N. Goodfellow13, R. Houlgatte11, James R. Hudson1, Susan E. Ide1, K. R. Iorio10, Wha‐Young Lee, N. Seki, Takahiro Nagase, K. Ishikawa, N. Nomura, Cheryl Phillips10, Mihael H. Polymeropoulos1, Mina Sandusky10, Karin Schmitt13, Richard Berry12, K. Swanson, R. Torres1, J. C. Venter10, James M. Sikela12, Jacques S. Beckmann, Jean Weissenbach, Richard M. Myers2, David R. Cox2, Michael R. James5, David Bentley4, Panos Deloukas4, Eric S. Lander3, Thomas J. Hudson14, Thomas J. Hudson3 
25 Oct 1996-Science
TL;DR: The gene map unifies the existing genetic and physical maps with the nucleotide and protein sequence databases in a fashion that should speed the discovery of genes underlying inherited human disease.
Abstract: The human genome is thought to harbor 50,000 to 100,000 genes, of which about half have been sampled to date in the form of expressed sequence tags. An international consortium was organized to develop and map gene-based sequence tagged site markers on a set of two radiation hybrid panels and a yeast artificial chromosome library. More than 16,000 human genes have been mapped relative to a framework map that contains about 1000 polymorphic genetic markers. The gene map unifies the existing genetic and physical maps with the nucleotide and protein sequence databases in a fashion that should speed the discovery of genes underlying inherited human disease. The integrated resource is available through a site on the World Wide Web at http://www.ncbi.nlm.nih.gov/SCIENCE96/.

1,072 citations

Journal ArticleDOI
29 Oct 1999-Science
TL;DR: The ages of individual X-Y gene pairs and the locations of their X members on the X chromosome were found to be highly correlated and age decreased in stepwise fashion from thedistal long arm to the distal short arm in at least four "evolutionary strata".
Abstract: Human sex chromosomes evolved from autosomes. Nineteen ancestral autosomal genes persist as differentiated homologs on the X and Y chromosomes. The ages of individual X-Y gene pairs (measured by nucleotide divergence) and the locations of their X members on the X chromosome were found to be highly correlated. Age decreased in stepwise fashion from the distal long arm to the distal short arm in at least four "evolutionary strata." Human sex chromosome evolution was probably punctuated by at least four events, each suppressing X-Y recombination in one stratum, without disturbing gene order on the X chromosome. The first event, which marked the beginnings of X-Y differentiation, occurred about 240 to 320 million years ago, shortly after divergence of the mammalian and avian lineages.

933 citations


Cited by
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Journal ArticleDOI
Eric S. Lander1, Lauren Linton1, Bruce W. Birren1, Chad Nusbaum1  +245 moreInstitutions (29)
15 Feb 2001-Nature
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

22,269 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Book ChapterDOI
TL;DR: This chapter assumes acquaintance with the principles and practice of PCR, as outlined in, for example, refs.
Abstract: 1. Introduction Designing PCR and sequencing primers are essential activities for molecular biologists around the world. This chapter assumes acquaintance with the principles and practice of PCR, as outlined in, for example, refs. 1–4. Primer3 is a computer program that suggests PCR primers for a variety of applications, for example to create STSs (sequence tagged sites) for radiation hybrid mapping (5), or to amplify sequences for single nucleotide polymor-phism discovery (6). Primer3 can also select single primers for sequencing reactions and can design oligonucleotide hybridization probes. In selecting oligos for primers or hybridization probes, Primer3 can consider many factors. These include oligo melting temperature, length, GC content , 3′ stability, estimated secondary structure, the likelihood of annealing to or amplifying undesirable sequences (for example interspersed repeats), the likelihood of primer–dimer formation between two copies of the same primer, and the accuracy of the source sequence. In the design of primer pairs Primer3 can consider product size and melting temperature, the likelihood of primer– dimer formation between the two primers in the pair, the difference between primer melting temperatures, and primer location relative to particular regions of interest or to be avoided.

16,407 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
J. Craig Venter1, Mark Raymond Adams1, Eugene W. Myers1, Peter W. Li1  +269 moreInstitutions (12)
16 Feb 2001-Science
TL;DR: Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems are indicated.
Abstract: A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies-a whole-genome assembly and a regional chromosome assembly-were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional approximately 12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.

12,098 citations