2P013 A new approach to build 3D atomic model from single electron microsope image(01A. Protein: Structure,Poster)

Single electron electronics is now well developed, and allows the manipulation of electrons one-by-one as they tunnel on and off a nanoscale conducting island. In the past decade or so, there have been concerted efforts in several laboratories to construct single electron devices incorporating ferromagnetic components in order to introduce spin functionality. The use of ferromagnetic electrodes with a non-magnetic island can lead to spin accumulation on the island. On the other hand, making the dot also ferromagnetic introduces new physics such as tunnelling magnetoresistance enhancement in the cotunnelling regime and manifestations of the Kondo effect. Such nanoscale islands are also found to have long spin lifetimes. Conventional spintronics makes use of the average spin-polarization of a large ensemble of electrons: this new approach offers the prospect of accessing the quantum properties of the electron, and is a candidate approach to the construction of solid-state spin-based qubits.

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TOUCHSTONE II: A New Approach to Ab Initio Protein Structure Prediction

Biophysical Journal ◽

10.1016/s0006-3495(03)74551-2 ◽

2003 ◽

Vol 85 (2) ◽

pp. 1145-1164 ◽

Cited By ~ 187

Author(s):

Yang Zhang ◽

Andrzej Kolinski ◽

Jeffrey Skolnick

Keyword(s):

Protein Structure ◽

Ab Initio ◽

Protein Structure Prediction ◽

Structure Prediction ◽

New Approach

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In-silico study of small cell lung cancer based on protein structure and function: A new approach to mimic biological system

Journal of Advanced Pharmaceutical Technology amp Research ◽

10.4103/2231-4040.161513 ◽

2015 ◽

Vol 6 (3) ◽

pp. 125

Author(s):

Nidhi Sood ◽

Sameer Chaudhary ◽

Tanvee Pardeshi ◽

Shama Mujawar ◽

KrishnaBalaji Deshmukh ◽

...

Keyword(s):

Lung Cancer ◽

Protein Structure ◽

Biological System ◽

In Silico ◽

Structure And Function ◽

Small Cell ◽

Small Cell Lung ◽

New Approach ◽

In Silico Study ◽

And Function

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Amino acid torsion angles enable prediction of protein fold classification

Scientific Reports ◽

10.1038/s41598-020-78465-1 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Kun Tian ◽

Xin Zhao ◽

Xiaogeng Wan ◽

Stephen S.-T. Yau

Keyword(s):

Protein Structure ◽

Amino Acid ◽

Protein Structure Prediction ◽

Structure Prediction ◽

High Throughput Sequencing ◽

Protein Structures ◽

Amino Acid Sequences ◽

Single Amino Acid ◽

New Approach ◽

Protein Functions

AbstractProtein structure can provide insights that help biologists to predict and understand protein functions and interactions. However, the number of known protein structures has not kept pace with the number of protein sequences determined by high-throughput sequencing. Current techniques used to determine the structure of proteins are complex and require a lot of time to analyze the experimental results, especially for large protein molecules. The limitations of these methods have motivated us to create a new approach for protein structure prediction. Here we describe a new approach to predict of protein structures and structure classes from amino acid sequences. Our prediction model performs well in comparison with previous methods when applied to the structural classification of two CATH datasets with more than 5000 protein domains. The average accuracy is 92.5% for structure classification, which is higher than that of previous research. We also used our model to predict four known protein structures with a single amino acid sequence, while many other existing methods could only obtain one possible structure for a given sequence. The results show that our method provides a new effective and reliable tool for protein structure prediction research.

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