A graphical model for protein secondary structure prediction

By Wei Chu, Zoubin Ghahramani, David L. Wild. 2004

43 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

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

In Materials Chemistry

1. Jinbo Xu
2. Jian Peng
3. Liefeng Bo
4. Sheng Wang
5. Jianzhu Ma
6. Siqi Sun
7. Zhiyong Wang
8. Liisa Holm

In Molecular Biology

1. Jinbo Xu
2. Jian Peng
3. Sheng Wang
4. Liefeng Bo
5. Jianzhu Ma
6. Badri Adhikari
7. Yang Zhang
8. Siqi Sun

Citations in the corpus

• Conditional Neural Fields (2009, methodology): “CRF, neural networks, Semi-Markov HMM [25], SVMpsi [24], PSIPRED[2] and CNF use the sequence profile generated by PSI-BLAST as described above.”
• Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs) (2006, unknown): “Recently, Liu et al. (2004) applied conditional random fields (CRFs), a discriminative graphical model based on undirected graphs, for protein secondary structure prediction; Chu et al. (2004) extended the segmental semi-Markov model (SSMM) under the Baysian framework for predicting protein second”