scispace - formally typeset
Search or ask a question
Institution

Applied Biosystems

About: Applied Biosystems is a based out in . It is known for research contribution in the topics: Mass spectrometry & Nucleic acid. The organization has 1521 authors who have published 1579 publications receiving 285423 citations.


Papers
More filters
Journal ArticleDOI
24 May 2011-Leukemia
TL;DR: The identification of >1000 miR genes expressed in different types of ALL forms a comprehensive repository for further functional studies that address the role of miRNAs in the biology of ALL.
Abstract: MicroRNAs (miRNAs) relevant to acute lymphoblastic leukemia (ALL) in children are hypothesized to be largely unknown as most miRNAs have been identified in non-leukemic tissues. In order to discover these miRNAs, we applied high-throughput sequencing to pooled fractions of leukemic cells obtained from 89 pediatric cases covering seven well-defined genetic types of ALL and normal hematopoietic cells. This resulted into 78 million small RNA reads representing 554 known, 28 novel and 431 candidate novel miR genes. In all, 153 known, 16 novel and 170 candidate novel mature miRNAs and miRNA-star strands were only expressed in ALL, whereas 140 known, 2 novel and 82 candidate novel mature miRNAs and miRNA-star strands were unique to normal hematopoietic cells. Stem-loop reverse transcriptase (RT)-quantitative PCR analyses confirmed the differential expression of selected mature miRNAs in ALL types and normal cells. Expression of 14 new miRNAs inversely correlated with expression of predicted target genes (-0.49 ≤ Spearman's correlation coefficients (Rs)≤ -0.27, P ≤ 0.05); among others, low levels of novel sol-miR-23 associated with high levels of its predicted (antiapoptotic) target BCL2 (B-cell lymphoma 2) in precursor B-ALL (Rs -0.36, P = 0.007). The identification of >1000 miR genes expressed in different types of ALL forms a comprehensive repository for further functional studies that address the role of miRNAs in the biology of ALL.

93 citations

Journal ArticleDOI
TL;DR: AFLP proved to be the most universal method, combining a phylogeny-building capacity similar to that of MLST with a much higher resolution, however, it had a lower reproducibility than sequencing-based MLST, DLST, and spa typing.
Abstract: The genetic determinants and phenotypic traits which make a Staphylococcus aureus strain a successful colonizer are largely unknown. The genetic diversity and population structure of 133 S. aureus isolates from healthy, generally risk-free adult carriers were investigated using four different typing methods: multilocus sequence typing (MLST), amplified fragment length polymorphism analysis (AFLP), double-locus sequence typing (DLST), and spa typing were compared. Carriage isolates displayed great genetic diversity which could only be revealed fully by DLST. Results of AFLP and MLST were highly concordant in the delineation of genotypic clusters of closely related isolates, roughly equivalent to clonal complexes. spa typing and DLST provided considerably less phylogenetic information. The resolution of spa typing was similar to that of AFLP and inferior to that of DLST. AFLP proved to be the most universal method, combining a phylogeny-building capacity similar to that of MLST with a much higher resolution. However, it had a lower reproducibility than sequencing-based MLST, DLST, and spa typing. We found two cases of methicillin-resistant S. aureus colonization, both of which were most likely associated with employment at a health service. Of 21 genotypic clusters detected, 2 were most prevalent: cluster 45 and cluster 30 each colonized 24% of the carrier population. The number of bacteria found in nasal samples varied significantly among the clusters, but the most prevalent clusters were not particularly numerous in the nasal samples. We did not find much evidence that genotypic clusters were associated with different carrier characteristics, such as age, sex, medical conditions, or antibiotic use. This may provide empirical support for the idea that genetic clusters in bacteria are maintained in the absence of adaptation to different niches. Alternatively, carrier characteristics other than those evaluated here or factors other than human hosts may exert selective pressure maintaining genotypic clusters.

93 citations

Journal ArticleDOI
TL;DR: A peptide, named “Akt-in” (Akt inhibitor, NH2-AVTDHPDRLWAWEKF-COOH), interacted with Akt and specifically inhibited its kinase activity, becoming the first molecule to demonstrate specific Akt kinase inhibition potency.

93 citations

Journal ArticleDOI
17 Oct 2007-PLOS ONE
TL;DR: The classifier genes identified in this study, and validated by TaqMan® real-time PCR, define a set of promising potential diagnostic markers, setting the stage for a blood-based gene expression test to facilitate early detection of TAA.
Abstract: Background Thoracic aortic aneurysm (TAA) is usually asymptomatic and associated with high mortality. Adverse clinical outcome of TAA is preventable by elective surgical repair; however, identifying at-risk individuals is difficult. We hypothesized that gene expression patterns in peripheral blood cells may correlate with TAA disease status. Our goal was to identify a distinct gene expression signature in peripheral blood that may identify individuals at risk for TAA. Methods and Findings Whole genome gene expression profiles from 94 peripheral blood samples (collected from 58 individuals with TAA and 36 controls) were analyzed. Significance Analysis of Microarray (SAM) identified potential signature genes characterizing TAA vs. normal, ascending vs. descending TAA, and sporadic vs. familial TAA. Using a training set containing 36 TAA patients and 25 controls, a 41-gene classification model was constructed for detecting TAA status and an overall accuracy of 78±6% was achieved. Testing this classifier on an independent validation set containing 22 TAA samples and 11 controls yielded an overall classification accuracy of 78%. These 41 classifier genes were further validated by TaqMan® real-time PCR assays. Classification based on the TaqMan® data replicated the microarray results and achieved 80% classification accuracy on the testing set. Conclusions This study identified informative gene expression signatures in peripheral blood cells that can characterize TAA status and subtypes of TAA. Moreover, a 41-gene classifier based on expression signature can identify TAA patients with high accuracy. The transcriptional programs in peripheral blood leading to the identification of these markers also provide insights into the mechanism of development of aortic aneurysms and highlight potential targets for therapeutic intervention. The classifier genes identified in this study, and validated by TaqMan® real-time PCR, define a set of promising potential diagnostic markers, setting the stage for a blood-based gene expression test to facilitate early detection of TAA.

92 citations

Patent
21 Mar 1994
TL;DR: In this article, the presence of a target nucleic acid is determined by detection of the ligated first and second oligonucleotides via the formation of a phosphoramidate linkage.
Abstract: Method and kits are provided for detecting one or more target nucleic acids. A first oligonucleotide having a 3' amino group and a second oligonucleotide having a 5' phosphate group are annealed to a contiguous complementary region of a target nucleic acid. Whenever the 3' terminal nucleotides of the first oligonucleotide and the 5' nucleotides of the second oligonucleotide are complementary to the opposing nucleotides on the target nucleic acid, a nucleic acid ligase ligates the first and second oligonucleotides via the formation of a phosphoramidate linkage. The presence of the target nucleic acid is determined by detection of the ligated first and second oligonucleotides.

92 citations


Authors

Showing all 1521 results

NameH-indexPapersCitations
Richard A. Gibbs172889249708
Friedrich C. Luft113109547619
Alexander N. Glazer7120821068
Vineet Bafna6823642574
Kevin R. Coombes6330823592
Darryl J. Pappin6117029409
Mark D. Johnson6028916103
György Marko-Varga5640912600
Paul Thomas5612844810
Gerald Zon5525611126
Michael W. Hunkapiller5113029756
Bjarni V. Halldorsson5114513180
David H. Hawke501579824
Ellson Y. Chen507128836
Sridhar Hannenhalli4916221959
Network Information
Related Institutions (5)
Genentech
17.1K papers, 1.4M citations

88% related

National Institutes of Health
297.8K papers, 21.3M citations

86% related

Scripps Research Institute
32.8K papers, 2.9M citations

86% related

Hoffmann-La Roche
43K papers, 1.6M citations

85% related

Wellcome Trust Sanger Institute
9.6K papers, 1.2M citations

85% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20182
20171
20164
20152
20147
201313