Abstract. Protein fold recognition is a key step to- wards inferring the tertiary structures from amino-acid sequences. Complex folds such as.

In this paper, we propose a chain graph model built on a causally connected series of segmentation conditional random fields (SCRFs) to address these issues.

We applied this model to predict β-helices and leucine-rich repeats, and found it significantly outperforms extant methods in predictive accuracy and/or ...

In this pa- per, we propose a chain graph model built on a causally connected series of segmentation conditional random fields (SCRFs) to address these issues.

Predicting Protein Folds with Structural Repeats Using a Chain Graph Model. Repeat I. Repeat 2. Repeat 3. Figure 1. Typical 3-D structure of proteins with 8- ...

Dec 31, 1984 · We applied this model to predict β-helices and leucine-rich repeats, and found it significantly outperforms extant methods in predictive ...

Aug 14, 2024 · The artificial intelligence (AI) system that solved the long-standing challenge of predicting the three-dimensional structure of proteins.

Sep 16, 2023 · The folded structures of proteins can be accurately predicted by deep learning algorithms from their amino-acid sequences.

Feb 7, 2024 · Here we present CombFold, a combinatorial and hierarchical assembly algorithm for predicting structures of large protein complexes utilizing pairwise ...

Mar 6, 2024 · We aim to provide a suitable approach, which processes the growing number of large protein complexes, to obtain biologically meaningful information.