Generalized Modular Spectrometers Combining a Compact Nanobeam Microcavity and Computational Reconstruction

ACS Photonics ◽  
2021 ◽  
Author(s):  
Ziwei Cheng ◽  
Yuhe Zhao ◽  
Jiahui Zhang ◽  
Hailong Zhou ◽  
Dingshan Gao ◽  
...  
Keyword(s):  
Computational Reconstruction

A Computational Reconstruction of the Adult Human Heart Transcriptional Profile

2000 ◽  
Vol 32 (11) ◽  
pp. 1931-1938 ◽  
Author(s):  
Stefania Bortoluzzi ◽  
Fabio d»Alessi ◽  
Gian Antonio Danieli
Keyword(s):  
Human Heart ◽  
Transcriptional Profile ◽  
Adult Human ◽  
Computational Reconstruction

scholarly journals Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

2021 ◽  
Author(s):  
Chen Cao ◽  
Jingni He ◽  
Lauren Mak ◽  
Deshan Perera ◽  
Devin Kwok ◽  
...  
Keyword(s):  
Single Molecule ◽  
Human Genetics ◽  
Real Data ◽  
Sequencing Technologies ◽  
Bacterial Genomics ◽  
Physical Linkage ◽  
Pooled Sequencing ◽  
Computational Reconstruction ◽  
Host Genetic ◽  
Host Evolution

Abstract DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

scholarly journals Aggregation of Omic Data and Secretome Prediction Enable the Discovery of Candidate Plasma Biomarkers for Beef Tenderness

2020 ◽  
Vol 21 (2) ◽  
pp. 664 ◽  
Author(s):  
Sabrina Boudon ◽  
Joelle Henry-Berger ◽  
Isabelle Cassar-Malek
Keyword(s):  
Plasma Proteins ◽  
Biological Information ◽  
Plasma Proteome ◽  
Complex Phenotype ◽  
Beef Tenderness ◽  
Plasma Biomarkers ◽  
Bovine Plasma ◽  
Computational Reconstruction ◽  
Beef Sector ◽  
Omic Data

Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sector. We hypothesized that publicly available data may help us discovering candidate plasma biomarkers. Thanks to a review of the literature, we built a corpus of articles on beef tenderness. Following data collection, aggregation, and computational reconstruction of the muscle secretome, the putative plasma proteins were searched by comparison with a bovine plasma proteome atlas and submitted to mining of biological information. Of the 44 publications included in the study, 469 unique gene names were extracted for aggregation. Seventy-one proteins putatively released in the plasma were revealed. Among them 13 proteins were predicted to be secreted in plasma, 44 proteins as hypothetically secreted in plasma, and 14 additional candidate proteins were detected thanks to network analysis. Among these 71 proteins, 24 were included in tenderness quantitative trait loci. The in-silico workflow enabled the discovery of candidate plasma biomarkers for beef tenderness from reconstruction of the secretome, to be examined in the cattle plasma proteome.

Computational Reconstruction of Protein Interaction Networks

2011 ◽  
pp. 155-180
Author(s):  
Konrad Mönks ◽  
Irmgard Mühlberger ◽  
Andreas Bernthaler ◽  
Raul Fechete ◽  
Paul Perco ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Computational Reconstruction

scholarly journals Computational Reconstruction of Ancestral DNA Sequences

2008 ◽  
pp. 171-184 ◽  
Author(s):  
Mathauieu Blanchette ◽  
Abdoulaye Baniré Diallo ◽  
Eric D. Green ◽  
Webb Miller ◽  
David Haussler
Keyword(s):  
Dna Sequences ◽  
Computational Reconstruction
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