Computer Analysis of Protein Sequencing Data

Proteins ◽  
1987 ◽  
pp. 455-460
Author(s):  
Norman Froelich ◽  
Lynn C. Williams ◽  
John T. Casagrande ◽  
Minnie McMillan
Keyword(s):  
Computer Analysis ◽  
Protein Sequencing ◽  
Sequencing Data

A Benchmark of Structural Variant Analysis Tools for Next Generation Sequencing Data

2013 ◽  
Vol 2 (4) ◽  
pp. 86-98
Author(s):  
Chatzinikolaou Panagiotis ◽  
Makris Christos ◽  
Dimitrios Vlachakis ◽  
Sophia Kossida
Keyword(s):  
Next Generation Sequencing ◽  
Level Structure ◽  
Atomic Level ◽  
Protein Sequencing ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Variant Analysis ◽  
Generation Sequencing

In language of genetics and biochemistry, sequencing is the determination of an unbranched biopolymer's primary structure. A sequence is a symbolic linear depiction, result of sequencing. This sequence is a succinct summary of the most of the sequenced molecule's atomic-level structure. (Most known is DNA-sequencing, RNA-sequencing, Protein-sequencing and Next-Generation-sequencing)

Integrated Computer Analysis of Genomic Sequencing Data Based on ICGenomics Tool

2020 ◽  
pp. 154-164
Author(s):  
Yuriy L. Orlov ◽  
Anatoly O. Bragin ◽  
Roman O. Babenko ◽  
Alina E. Dresvyannikova ◽  
Sergey S. Kovalev ◽  
...  
Keyword(s):  
Computer Analysis ◽  
Genomic Sequencing ◽  
Sequencing Data

scholarly journals Identification and Characterization of New Laccase Biocatalysts from Pseudomonas Species Suitable for Degradation of Synthetic Textile Dyes

Catalysts ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 629 ◽  
Author(s):  
Mina Mandic ◽  
Lidija Djokic ◽  
Efstratios Nikolaivits ◽  
Radivoje Prodanovic ◽  
Kevin O’Connor ◽  
...  
Keyword(s):  
Posttranslational Modifications ◽  
Textile Dyes ◽  
Protein Sequencing ◽  
Heterologous Protein Expression ◽  
Reactive Black 5 ◽  
Sequencing Data ◽  
Genetic Manipulations ◽  
Amido Black 10B ◽  
Ph Range

Laccases are multicopper-oxidases with variety of biotechnological applications. While predominantly used, fungal laccases have limitations such as narrow pH and temperature range and their production via heterologous protein expression is more complex due to posttranslational modifications. In comparison, bacterial enzymes, including laccases, usually possess higher thermal and pH stability, and are more suitable for expression and genetic manipulations in bacterial expression hosts. Therefore, the aim of this study was to identify, recombinantly express, and characterize novel laccases from Pseudomonas spp. A combination of approaches including DNA sequence analysis, N-terminal protein sequencing, and genome sequencing data analysis for laccase amplification, cloning, and overexpression have been used. Four active recombinant laccases were obtained, one each from P. putida KT2440 and P. putida CA-3, and two from P. putida F6. The new laccases exhibited broad temperature and pH range and high thermal stability, as well as the potential to degrade selection of synthetic textile dyes. The best performing laccase was CopA from P. putida F6 which degraded five out of seven tested dyes, including Amido Black 10B, Brom Cresol Purple, Evans Blue, Reactive Black 5, and Remazol Brilliant Blue. This work highlighted species of Pseudomonas genus as still being good sources of biocatalytically relevant enzymes.

scholarly journals Variant-driven multi-wave pattern of COVID-19 via Machine Learning clustering of spike protein mutations

2021 ◽  
Author(s):  
Adele de Hoffer ◽  
Shahram Vatani ◽  
Corentin Cot ◽  
Giacomo Cacciapaglia ◽  
Francesco Conventi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Temporal Structure ◽  
Wave Pattern ◽  
Protein Sequencing ◽  
Host Cells ◽  
Spike Protein ◽  
Sequencing Data ◽  
Current Case ◽  
The Uk

Never before such a vast amount of data has been collected for any viral pandemic than for the current case of COVID-19. This offers the possibility to answer a number of highly relevant questions, regarding the evolution of the virus and the role mutations play in its spread among the population. We focus on spike proteins, as they bear the main responsibility for the effectiveness of the virus diffusion by controlling the interactions with the host cells. Using the available temporal structure of the sequencing data for the SARS-CoV-2 spike protein in the UK, we demonstrate that every wave of the pandemic is dominated by a different variant. Consequently, the time evolution of each variant follows a temporal structure encoded in the epidemiological Renormalisation Group approach to compartmental models. Machine learning is the tool of choice to determine the variants at play, independent of (but complementary to) the virological classification. Our Machine Learning algorithm on spike protein sequencing provides a simple and unbiased way to identify, classify and track relevant virus variants without any prior knowledge of their characteristics. Hence, we propose a new tool that can help preventing and forecasting the emergence of new waves, and that can be used by decision makers to define short and long term strategies to curb the current COVID-19 pandemic or future ones.

scholarly journals Learning dynamical information from static protein and sequencing data

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Philip Pearce ◽  
Francis G. Woodhouse ◽  
Aden Forrow ◽  
Ashley Kelly ◽  
Halim Kusumaatmaja ◽  
...  
Keyword(s):  
Protein Folding ◽  
Phylogenetic Trees ◽  
Network Dynamics ◽  
Protein Sequencing ◽  
Stochastic Simulations ◽  
High Dimensional ◽  
Sequencing Data ◽  
Generic Structure ◽  
Complex Processes ◽  
Neuronal Network Dynamics

AbstractMany complex processes, from protein folding to neuronal network dynamics, can be described as stochastic exploration of a high-dimensional energy landscape. Although efficient algorithms for cluster detection in high-dimensional spaces have been developed over the last two decades, considerably less is known about the reliable inference of state transition dynamics in such settings. Here we introduce a flexible and robust numerical framework to infer Markovian transition networks directly from time-independent data sampled from stationary equilibrium distributions. We demonstrate the practical potential of the inference scheme by reconstructing the network dynamics for several protein-folding transitions, gene-regulatory network motifs, and HIV evolution pathways. The predicted network topologies and relative transition time scales agree well with direct estimates from time-dependent molecular dynamics data, stochastic simulations, and phylogenetic trees, respectively. Owing to its generic structure, the framework introduced here will be applicable to high-throughput RNA and protein-sequencing datasets, and future cryo-electron microscopy (cryo-EM) data.

Computer analysis of side-band holography in STEM

1991 ◽  
Vol 49 ◽  
pp. 684-685
Author(s):  
M.A. Gribelyuk ◽  
J.M. Cowley
Keyword(s):  
Interference Pattern ◽  
Computer Analysis ◽  
Side Band ◽  
Diffraction Plane ◽  
Illumination System ◽  
Probe Size

Recently the use of a biprism in a STEM instrument has been suggested for recording of a hologram. A biprism is inserted in the illumination system and creates two coherent focussed beams at the specimen level with a probe size d= 5-10Å. If one beam passes through an object and another one passes in vacuum, an interference pattern, i.e. a hologram can be observed in diffraction plane (Fig.1).

Biotelemetry and Computer Analysis of Electrocardiograms

1969 ◽  
Vol 08 (03) ◽  
pp. 120-127 ◽  
Author(s):  
P. R. Amlinger
Keyword(s):  
Computer Analysis ◽  
Rural Areas ◽  
Applied Research ◽  
Research Effort ◽  
Pilot Project ◽  
Modern Medicine ◽  
Modern Technology ◽  
Long Distance ◽  
Regional Medical ◽  
Medical Program

Routine transmission of electrocardiograms and their computer interpretation via long-distance telephone lines has been proven feasible in the Automated Electrocardiogram Project of the Missouri Regional Medical Program. Though this Pilot Project — the first on a state-wide basis — is still viewed as an applied research effort rather than a service, such biotelemetry is rapidly gaining acceptance as a medium to bring modern medicine, through modern technology, to urban and remote rural areas as well, where it is most needed.The computer executes all the wave measuraments and calculations with incredible speed. It takes over a most boring, repetitive part of the physician’s work. However, it can only follow the instructions of the diagnostic program, compiled by expert cardiologists. Thus, it is an ever-ready, never-tiring servant for the physician and his patients.

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