A Short Report on the Relation between the mRNA Sequence and the Encoded Protein Structure

2014 ◽  
pp. 130-131
Author(s):  
Xiaojuan Shen ◽  
Yi Zhang ◽  
Guanglin Li
Keyword(s):  
Protein Structure ◽  
Short Report ◽  
Mrna Sequence

Acquisition of EELS spectra for high-resolution spectroscopy

1993 ◽  
Vol 51 ◽  
pp. 578-579
Author(s):  
Maoxu Qian ◽  
Mehmet Sarikaya ◽  
Edward A. Stern
Keyword(s):  
Energy Loss ◽  
Detection System ◽  
High Resolution Spectroscopy ◽  
High Signal ◽  
Short Report ◽  
Edge Structure ◽  
High Background ◽  
Gain Variation ◽  
Sufficient Energy ◽  
On Line

It is difficult, in general, to perform quantitative EELS to determine, for example, relative or absolute compositions of elements with relatively high atomic numbers (using, e.g., K edge energies from 500 eV to 2000 eV), to study ELNES (energy loss near edge structure) signal using the white lines to determine oxidation states, and to analyze EXELFS (extended energy loss fine structure) to study short range ordering. In all these cases, it is essential to have high signal-to-noise (S/N) ratio (low systematical error) with high overall counts, and sufficient energy resolution (∽ 1 eV), requirements which are, in general, difficult to attain. The reason is mainly due to three important inherent limitations in spectrum acquisition with EELS in the TEM. These are (i) large intrinsic background in EELS spectra, (ii) channel-to-channel gain variation (CCGV) in the parallel detection system, and (iii) difficulties in obtaining statistically high total counts (∽106) per channel (CH). Except the high background in the EELS spectrum, the last two limitations may be circumvented, and the S/N ratio may be attained by the improvement in the on-line acquisition procedures. This short report addresses such procedures.

Sequence Specific Dihedral Angle Distribution: Application in Protein Structure Prediction and Evaluation

1970 ◽  
Vol 19 (2) ◽  
pp. 217-226
Author(s):  
S. M. Minhaz Ud-Dean ◽  
Mahdi Muhammad Moosa
Keyword(s):  
Protein Structure ◽  
Dihedral Angle ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Protein Structures ◽  
Angle Distribution ◽  
Ramachandran Plot ◽  
Specific Data ◽  
Specific Distribution ◽  
Structure Evaluation

Protein structure prediction and evaluation is one of the major fields of computational biology. Estimation of dihedral angle can provide information about the acceptability of both theoretically predicted and experimentally determined structures. Here we report on the sequence specific dihedral angle distribution of high resolution protein structures available in PDB and have developed Sasichandran, a tool for sequence specific dihedral angle prediction and structure evaluation. This tool will allow evaluation of a protein structure in pdb format from the sequence specific distribution of Ramachandran angles. Additionally, it will allow retrieval of the most probable Ramachandran angles for a given sequence along with the sequence specific data. Key words: Torsion angle, φ-ψ distribution, sequence specific ramachandran plot, Ramasekharan, protein structure appraisal D.O.I. 10.3329/ptcb.v19i2.5439 Plant Tissue Cult. & Biotech. 19(2): 217-226, 2009 (December)

Protein structure prediction of human connexin 30 and its mutations in hearing system

2014 ◽  
Vol 3 (5) ◽  
Author(s):  
S. Reiisi ◽  
M. Hashemzade-chaleshtori ◽  
S. Reisi ◽  
H. Shahi ◽  
S. Parchami ◽  
...  
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Connexin 30 ◽  
Hearing System
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