Table 1.

Fragment-based local structure prediction methods. The table gives the list of methods for predicting local backbone conformation based on a library of fragments (prototypes). The length, number of prototypes and the distance measure used to generate the library are also mentioned. The reported prediction rates from the original publication are also listed. MDA, maximum deviation in torsion angles; ANN, artificial neural networks; SVM, support vector machines.

research team	fragment length	distance measure	prediction method	prototype number	prediction rate (%)
Rooman et al.	4, 5, 6, 7	Cα RMSD	statistical mechanics (mean force potential)	4	40–47
Bystroff & Baker	3–19	sequence profiles, RMSD, MDA	profile–profile matching	13 (later updated to 16)	50
de Brevern et al.	5	dihedral angles	Bayesian	16	34.4
Hunter & Subramaniam	7	hypercosine Cα	Bayesian	28–16336	40
Yang & Wang	9	dihedral angles	sequence profile matching	138604	79
Etchebest et al.	5	dihedral angles	Bayesian (simulated annealing)	16 [153]	49
Benros et al.	11	Cα RMSD, PB based	hybrid protein model	120	51.2
Sander et al.	7	Cα distance	decision trees, SVM, random forest	28	23–36
Dong et al.	7	Cα distance	ANN	28	45.6
Dong et al.	5	dihedral angles	ANN	16 [153]	58.5
Zimmermann et al.	5	dihedral angles	SVM	16 [153]	61
Chen & Johnson	9	Cα distance	SVM	800	72
Bornot et al.	11	Cα RMSD, PB based	hybrid protein model	120	63.1
Rangwala et al.	5	dihedral angles	SVM	16 [153]	67
Yu et al.	7–19	dihedral angles	Bayesian	82	62