scholarly journals Identification and characterization of a 19q12 amplicon in esophageal adenocarcinomas using two-dimensional genomic scanning and amplification mapping of sequence tagged sites

10.1038/87174 ◽  
2001 ◽  
Vol 27 (S4) ◽  
pp. 67-68
Author(s):  
Lin Lin ◽  
Michael Prescott ◽  
Rork Kuick ◽  
Samir Hanash ◽  
Mark Orringer ◽  
...  
Keyword(s):  
Two Dimensional ◽  
Sequence Tagged Sites ◽  
Identification And Characterization

Identification and characterization of heat shock protein 27 protein species in human myocardial two-dimensional electrophoresis patterns

1997 ◽  
Vol 18 (15) ◽  
pp. 2823-2831 ◽  
Author(s):  
Christian Scheler ◽  
Eva-Christina Müller ◽  
Joachim Stahl ◽  
Ursula Müller-Werdan ◽  
Johann Salnikow ◽  
...  
Keyword(s):  
Heat Shock ◽  
Heat Shock Protein ◽  
Heat Shock Protein 27 ◽  
Two Dimensional ◽  
Protein Species ◽  
Two Dimensional Electrophoresis ◽  
Identification And Characterization ◽  
Dimensional Electrophoresis

scholarly journals DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Da-Wei Li ◽  
Alexandar L. Hansen ◽  
Chunhua Yuan ◽  
Lei Bruschweiler-Li ◽  
Rafael Brüschweiler
Keyword(s):  
Neural Network ◽  
Nmr Spectra ◽  
Deep Neural Network ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Two Dimensional ◽  
Molecular Systems ◽  
Intrinsically Disordered ◽  
Identification And Characterization

AbstractThe analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was trained on a large number of synthetic spectra of known composition with variable degrees of crowdedness. We show that our method is able to correctly identify overlapping peaks, including ones that are challenging for expert spectroscopists and existing computational methods alike. We demonstrate the utility of DEEP Picker on NMR spectra of folded and intrinsically disordered proteins as well as a complex metabolomics mixture, and show how it provides access to valuable NMR information. DEEP Picker should facilitate the semi-automation and standardization of protocols for better consistency and sharing of results within the scientific community.

scholarly journals IDENTIFICATION AND CHARACTERIZATION OF THE alc GENE PRODUCT OF BACTERIOPHAGE T4

Genetics ◽  
1984 ◽  
Vol 108 (2) ◽  
pp. 291-304
Author(s):  
Elizabeth Kutter ◽  
Rolf Drivdahl ◽  
Keith Rand
Keyword(s):  
Rna Polymerase ◽  
Gene Product ◽  
Dna Sequence ◽  
Bacteriophage T4 ◽  
Two Dimensional ◽  
Phage Dna ◽  
Precise Mapping ◽  
Identification And Characterization ◽  
Α Subunits

ABSTRACT Bacteriophage T4 infection rapidly and almost completely inhibits transcription of host and other phage DNAs. Two processes have been implicated to date in this inhibition: (1) ADP ribosylation of the α subunits of the RNA polymerase, involving gp alt (which is injected with the phage DNA) and, later, gp mod; and (2) the action of the T4 alc/unf gene product, synthesized immediately after infection. The latter unfolds the host genome and also blocks transcription of cytosine-containing DNA. Here, we describe the identification on two-dimensional polyacrylamide gels of gp alc/unf, the more precise mapping of the gene and the identification and analysis of the appropriate DNA sequence from an Unf+  alc mutant.

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