86 related articles for article (PubMed ID: 12723687)
1. Recognition of adenosine triphosphate binding sites using parallel cascade system identification.
Green JR; Korenberg MJ; David R; Hunter IW
Ann Biomed Eng; 2003 Apr; 31(4):462-70. PubMed ID: 12723687
[TBL] [Abstract][Full Text] [Related]
2. Automatic classification of protein sequences into structure/function groups via parallel cascade identification: a feasibility study.
Korenberg MJ; David R; Hunter IW; Solomon JE
Ann Biomed Eng; 2000 Jul; 28(7):803-11. PubMed ID: 11016417
[TBL] [Abstract][Full Text] [Related]
3. Neural networks for protein classification.
Weinert WR; Lopes HS
Appl Bioinformatics; 2004; 3(1):41-8. PubMed ID: 16323965
[TBL] [Abstract][Full Text] [Related]
4. Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification.
Huang CD; Lin CT; Pal NR
IEEE Trans Nanobioscience; 2003 Dec; 2(4):221-32. PubMed ID: 15376912
[TBL] [Abstract][Full Text] [Related]
5. SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition.
Melvin I; Ie E; Kuang R; Weston J; Stafford WN; Leslie C
BMC Bioinformatics; 2007 May; 8 Suppl 4(Suppl 4):S2. PubMed ID: 17570145
[TBL] [Abstract][Full Text] [Related]
6. On the advantages of multi-input single-output parallel cascade classifiers.
Green JR; Korenberg MJ
Ann Biomed Eng; 2006 Apr; 34(4):709-16. PubMed ID: 16538545
[TBL] [Abstract][Full Text] [Related]
7. Classification of protein quaternary structure with support vector machine.
Zhang SW; Pan Q; Zhang HC; Zhang YL; Wang HY
Bioinformatics; 2003 Dec; 19(18):2390-6. PubMed ID: 14668222
[TBL] [Abstract][Full Text] [Related]
8. Prediction of protein structure classes with flexible neural tree.
Bao W; Chen Y; Wang D
Biomed Mater Eng; 2014; 24(6):3797-806. PubMed ID: 25227096
[TBL] [Abstract][Full Text] [Related]
9. Why neural networks should not be used for HIV-1 protease cleavage site prediction.
Rögnvaldsson T; You L
Bioinformatics; 2004 Jul; 20(11):1702-9. PubMed ID: 14988129
[TBL] [Abstract][Full Text] [Related]
10. Parallel cascade recognition of exon and intron DNA sequences.
Korenberg MJ; Lipson ED; Green JR; Solomon JE
Ann Biomed Eng; 2002 Jan; 30(1):129-40. PubMed ID: 11874136
[TBL] [Abstract][Full Text] [Related]
11. PCI-SS: MISO dynamic nonlinear protein secondary structure prediction.
Green JR; Korenberg MJ; Aboul-Magd MO
BMC Bioinformatics; 2009 Jul; 10():222. PubMed ID: 19615046
[TBL] [Abstract][Full Text] [Related]
12. A nearest neighbor approach for automated transporter prediction and categorization from protein sequences.
Li H; Dai X; Zhao X
Bioinformatics; 2008 May; 24(9):1129-36. PubMed ID: 18337257
[TBL] [Abstract][Full Text] [Related]
13. A naive Bayes model to predict coupling between seven transmembrane domain receptors and G-proteins.
Cao J; Panetta R; Yue S; Steyaert A; Young-Bellido M; Ahmad S
Bioinformatics; 2003 Jan; 19(2):234-40. PubMed ID: 12538244
[TBL] [Abstract][Full Text] [Related]
14. Automated generation and refinement of protein signatures: case study with G-protein coupled receptors.
Sadowski MI; Parish JH
Bioinformatics; 2003 Apr; 19(6):727-34. PubMed ID: 12691984
[TBL] [Abstract][Full Text] [Related]
15. Combining classifiers for improved classification of proteins from sequence or structure.
Melvin I; Weston J; Leslie CS; Noble WS
BMC Bioinformatics; 2008 Sep; 9():389. PubMed ID: 18808707
[TBL] [Abstract][Full Text] [Related]
16. Functional discrimination of membrane proteins using machine learning techniques.
Gromiha MM; Yabuki Y
BMC Bioinformatics; 2008 Mar; 9():135. PubMed ID: 18312695
[TBL] [Abstract][Full Text] [Related]
17. Prediction of protein structural class for the twilight zone sequences.
Kurgan L; Chen K
Biochem Biophys Res Commun; 2007 Jun; 357(2):453-60. PubMed ID: 17433260
[TBL] [Abstract][Full Text] [Related]
18. CASTOR: clustering algorithm for sequence taxonomical organization and relationships.
Liu AH; Califano A
J Comput Biol; 2003; 10(1):21-45. PubMed ID: 12676049
[TBL] [Abstract][Full Text] [Related]
19. HMM-ModE--improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying emission probabilities with negative training sequences.
Srivastava PK; Desai DK; Nandi S; Lynn AM
BMC Bioinformatics; 2007 Mar; 8():104. PubMed ID: 17389042
[TBL] [Abstract][Full Text] [Related]
20. Accuracy of structure-based sequence alignment of automatic methods.
Kim C; Lee B
BMC Bioinformatics; 2007 Sep; 8():355. PubMed ID: 17883866
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
