scholarly journals AGEpy: a Python package for computational biology

2018 ◽  
Author(s):  
Franziska Metge ◽  
Robert Sehlke ◽  
Jorge Boucas
Keyword(s):  
Computational Biology ◽  
Open Source ◽  
High Throughput ◽  
Biological Data ◽  
Command Line ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Link Type ◽  
Biological Meaning ◽  
Python Package

AbstractSummary:AGEpy is a Python package focused on the transformation of interpretable data into biological meaning. It is designed to support high-throughput analysis of pre-processed biological data using either local Python based processing or Python based API calls to local or remote servers. In this application note we describe its different Python modules as well as its command line accessible toolsaDiff,abed,blasto,david, andobo2tsv.Availability:The open source AGEpy Python package is freely available at:https://github.com/mpg-age-bioinformatics/AGEpy.Contact:[email protected]

scholarly journals Chewie Nomenclature Server (chewie-NS): a deployable nomenclature server for easy sharing of core and whole genome MLST schemas

2020 ◽  
Vol 49 (D1) ◽  
pp. D660-D666
Author(s):  
Rafael Mamede ◽  
Pedro Vila-Cerqueira ◽  
Mickael Silva ◽  
João A Carriço ◽  
Mário Ramirez
Keyword(s):  
High Throughput ◽  
Whole Genome ◽  
Command Line ◽  
Public Repository ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Comparison Of Results ◽  
Gene Typing ◽  
Rest Api ◽  
Command Line Version

Abstract Chewie Nomenclature Server (chewie-NS, https://chewbbaca.online/) allows users to share genome-based gene-by-gene typing schemas and to maintain a common nomenclature, simplifying the comparison of results. The combination between local analyses and a public repository of allelic data strikes a balance between potential confidentiality issues and the need to compare results. The possibility of deploying private instances of chewie-NS facilitates the creation of nomenclature servers with a restricted user base to allow compliance with the strictest data policies. Chewie-NS allows users to easily share their own schemas and to explore publicly available schemas, including informative statistics on schemas and loci presented in interactive charts and tables. Users can retrieve all the information necessary to run a schema locally or all the alleles identified at a particular locus. The integration with the chewBBACA suite enables users to directly upload new schemas to chewie-NS, download existing schemas and synchronize local and remote schemas from chewBBACA command line version, allowing an easier integration into high-throughput analysis pipelines. The same REST API linking chewie-NS and the chewBBACA suite supports the interaction of other interfaces or pipelines with the databases available at chewie-NS, facilitating the reusability of the stored data.

Combination of Free Software, Light Microscopy and Non-specific Dyes for a High-throughput Analysis in Live/Dead Cell Count

2015 ◽  
Vol 11 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Luciano Cardoso ◽  
Suellen Cordeiro ◽  
Marcio Fronza ◽  
Denise Endringer ◽  
Tadeu de Andrade ◽  
...  
Keyword(s):  
Light Microscopy ◽  
Cell Count ◽  
High Throughput ◽  
Free Software ◽  
Dead Cell ◽  
High Throughput Analysis ◽  
Throughput Analysis

Multiwell Combinatorial Hydrogel Array for High-Throughput Analysis of Cell–ECM Interactions

2021 ◽  
Author(s):  
Ruoxing Lei ◽  
Erin A. Akins ◽  
Kelly C. Y. Wong ◽  
Nicole A. Repina ◽  
Kayla J. Wolf ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Analysis ◽  
Throughput Analysis

Development of pattern recognition based on the nanosheet-DNA probes and an extendible DNA library

The Analyst ◽  
2021 ◽  
Author(s):  
Jiawei Qi ◽  
Pinhua Rao ◽  
Lele Wang ◽  
Li Xu ◽  
Yanli Wen ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
High Throughput ◽  
Analysis Data ◽  
Dna Probes ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Dna Library ◽  
Array Sensing

Pattern recognition, also called “array sensing” is a recognition strategy with a wide and expandable analysis range, based on the high-throughput analysis data. In this work, we constructed a sensor...

Highly Sensitive Detection of Paraquat with Pillar[5]arene as an aptamer in α-Hemolysin Nanopore

2021 ◽  
Author(s):  
Xiaojia Jiang ◽  
Mingsong Zang ◽  
Fei Li ◽  
Chunxi Hou ◽  
Quan Luo ◽  
...  
Keyword(s):  
Real Time ◽  
High Throughput ◽  
Single Molecule ◽  
Single Molecule Detection ◽  
Sensitive Detection ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
The Real ◽  
Highly Sensitive ◽  
Highly Sensitive Detection

Biological nanopore-based techniques have attracted more and more attention recently in the field of single-molecule detection, because they allow the real-time, sensitive, high-throughput analysis. Herein, we report an engineered biological...

High-Throughput Analysis of Ligand-Induced Internalization of β2-Adrenoceptors Using the Coiled-Coil Tag–Probe Method

2012 ◽  
Vol 84 (3) ◽  
pp. 1754-1759 ◽  
Author(s):  
Yuki Takeda ◽  
Yoshiaki Yano ◽  
Katsumi Matsuzaki
Keyword(s):  
High Throughput ◽  
Coiled Coil ◽  
Probe Method ◽  
High Throughput Analysis ◽  
Throughput Analysis

scholarly journals High-throughput analysis of high-molecular weight glutenin subunits in 665 wheat genotypes using an optimized MALDI-TOF–MS method

3 Biotech ◽  
2021 ◽  
Vol 11 (2) ◽  
Author(s):  
You-Ran Jang ◽  
Sewon Kim ◽  
Jae-Ryeong Sim ◽  
Su-Bin Lee ◽  
Sun-Hyung Lim ◽  
...  
Keyword(s):  
Molecular Weight ◽  
High Molecular Weight ◽  
High Throughput ◽  
Glutenin Subunits ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Maldi Tof Ms ◽  
Wheat Genotypes ◽  
Maldi Tof ◽  
Tof Ms

scholarly journals Software Tools for High-Throughput Analysis and Archiving of Immunohistochemistry Staining Data Obtained with Tissue Microarrays

2002 ◽  
Vol 161 (5) ◽  
pp. 1557-1565 ◽  
Author(s):  
Chih Long Liu ◽  
Wijan Prapong ◽  
Yasodha Natkunam ◽  
Ash Alizadeh ◽  
Kelli Montgomery ◽  
...  
Keyword(s):  
High Throughput ◽  
Tissue Microarrays ◽  
Software Tools ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Immunohistochemistry Staining
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