Agilent Technologies

About: Agilent Technologies is a company organization based out in Santa Clara, California, United States. It is known for research contribution in the topics: Signal & Mass spectrometry. The organization has 7398 authors who have published 11518 publications receiving 262410 citations. The organization is also known as: Agilent Technologies, Inc..

Synthetic chromosome arms function in yeast and generate phenotypic diversity by design

Abstract: Recent advances in DNA synthesis technology have enabled the construction of novel genetic pathways and genomic elements, furthering our understanding of system-level phenomena. The ability to synthesize large segments of DNA allows the engineering of pathways and genomes according to arbitrary sets of design principles. Here we describe a synthetic yeast genome project, Sc2.0, and the first partially synthetic eukaryotic chromosomes, Saccharomyces cerevisiae chromosome synIXR, and semi-synVIL. We defined three design principles for a synthetic genome as follows: first, it should result in a (near) wild-type phenotype and fitness; second, it should lack destabilizing elements such as tRNA genes or transposons; and third, it should have genetic flexibility to facilitate future studies. The synthetic genome features several systemic modifications complying with the design principles, including an inducible evolution system, SCRaMbLE (synthetic chromosome rearrangement and modification by loxP-mediated evolution). We show the utility of SCRaMbLE as a novel method of combinatorial mutagenesis, capable of generating complex genotypes and a broad variety of phenotypes. When complete, the fully synthetic genome will allow massive restructuring of the yeast genome, and may open the door to a new type of combinatorial genetics based entirely on variations in gene content and copy number.

Bio-microarray fabrication techniques--a review.

Abstract: Microarrays with biomolecules (e.g., DNA and proteins), cells, and tissues immobilized on solid substrates are important tools for biological research, including genomics, proteomics, and cell analysis. In this paper, the current state of microarray fabrication is reviewed. According to spot formation techniques, methods are categorized as "contact printing" and "non-contact printing." Contact printing is a widely used technology, comprising methods such as contact pin printing and microstamping. These methods have many advantages, including reproducibility of printed spots and facile maintenance, as well as drawbacks, including low-throughput fabrication of arrays. Non-contact printing techniques are newer and more varied, comprising photochemistry-based methods, laser writing, electrospray deposition, and inkjet technologies. These technologies emerged from other applications and have the potential to increase microarray fabrication throughput; however, there are several challenges in applying them to microarray fabrication, including interference from satellite drops and biomolecule denaturization.

The fine-scale and complex architecture of human copy-number variation.

Abstract: Despite considerable excitement over the potential functional significance of copy-number variants (CNVs), we still lack knowledge of the fine-scale architecture of the large majority of CNV regions in the human genome. In this study, we used a high-resolution array-based comparative genomic hybridization (aCGH) platform that targeted known CNV regions of the human genome at approximately 1 kb resolution to interrogate the genomic DNAs of 30 individuals from four HapMap populations. Our results revealed that 1020 of 1153 CNV loci (88%) were actually smaller in size than what is recorded in the Database of Genomic Variants based on previously published studies. A reduction in size of more than 50% was observed for 876 CNV regions (76%). We conclude that the total genomic content of currently known common human CNVs is likely smaller than previously thought. In addition, approximately 8% of the CNV regions observed in multiple individuals exhibited genomic architectural complexity in the form of smaller CNVs within larger ones and CNVs with interindividual variation in breakpoints. Future association studies that aim to capture the potential influences of CNVs on disease phenotypes will need to consider how to best ascertain this previously uncharacterized complexity.

An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: sensitivity and specificity analysis.

Abstract: MS/MS and associated database search algorithms are essential proteomic tools for identifying peptides. Due to their widespread use, it is now time to perform a systematic analysis of the various algorithms currently in use. Using blood specimens used in the HUPO Plasma Proteome Project, we have evaluated five search algorithms with respect to their sensitivity and specificity, and have also accurately benchmarked them based on specified false-positive (FP) rates. Spectrum Mill and SEQUEST performed well in terms of sensitivity, but were inferior to MASCOT, X!Tandem, and Sonar in terms of specificity. Overall, MASCOT, a probabilistic search algorithm, correctly identified most peptides based on a specified FP rate. The rescoring algorithm, PeptideProphet, enhanced the overall performance of the SEQUEST algorithm, as well as provided predictable FP error rates. Ideally, score thresholds should be calculated for each peptide spectrum or minimally, derived from a reversed-sequence search as demonstrated in this study based on a validated data set. The availability of open-source search algorithms, such as X!Tandem, makes it feasible to further improve the validation process (manual or automatic) on the basis of “consensus scoring”, i.e., the use of multiple (at least two) search algorithms to reduce the number of FPs.

Polyharmonic distortion modeling

Abstract: For more than a quarter of a century, microwave engineers have had the benefit of a foundation of mutually interacting components of measurement, modeling, and simulation to design and test linear components and systems. S-parameters are perhaps the most successful behavioral models ever. They have the powerful property that the S-parameters of individual components are sufficient to determine the S-parameters of any combination of those components. S-parameters of a component are sufficient to predict its response to any signal, provided only that the signal is of sufficiently small amplitude. We have presented the PHD modeling approach. It is a black-box frequency-domain model that provides a foundation for measurement, modeling, and simulation of driven nonlinear systems. The PHD model is very accurate for a wide variety of nonlinear characteristics, including compression, AM-PM, harmonics, load-pull, and time-domain waveforms. The PHD model faithfully represents driven nonlinear systems with mismatches at both the fundamental and harmonics. This enables the accurate simulation of distortion through cascaded chains of nonlinear components, thus providing key new design verification capabilities for RF and microwave modules and subsystems