REVIEW : Recent advances in developing web-servers for predicting protein attributes

By Kuo-Chen Chou, Hongbin Shen. 2009

473 citations recorded by the source corpus.

Recent advance in large-scale genome sequencing has generated a huge volume of protein sequences. In order to timely utilize the information hidden in these newly discovered sequences, it is highly desired to develop computational methods for efficiently identifying their various attributes because the information thus obtained will be very useful for both basic research and drug development. Particularly, it would be even more useful and welcome if a user-friendly web-server could be provided for each of these methods. In this minireview, a systematic introduction is presented to highlight the development of these web-servers by our group during the last three years.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/bdbeee63d6db461bbdf7267b8007800b1771e507

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Qiang Yang
2. Qian Xu
3. Sinno Jialin Pan
4. H. Xue
5. Kuo-Chen Chou
6. Hongbin Shen
7. Yu Zhang
8. Xuan Xiao

Citations in the corpus

• Some remarks on protein attribute prediction and pseudo amino acid composition (2010, methodology): “Tomakeanewpredictionmethodreallyusefulforthe majority of people, it is an important direction or necessary procedure to provide a user-friendly and publicly accessible web-server for the method (Chou and Shen, 2009).”
• Multitask Learning for Protein Subcellular Location Prediction (2011, background): “Ç 1INTRODUCTION O RGANELLES with different functions are specialized the importance of protein subcellular localization, consider­subunits in a cell.”