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PSLDoc: Protein subcellular localization prediction based on gapped-dipeptides and probabilistic latent semantic analysis.
Chang JM, Su EC, Lo A, Chiu HS, Sung TY, Hsu WL. Chang JM, et al. Among authors: lo a. Proteins. 2008 Aug;72(2):693-710. doi: 10.1002/prot.21944. Proteins. 2008. PMID: 18260102
We present PSLDoc, a method based on gapped-dipeptides and probabilistic latent semantic analysis (PLSA) to solve this problem. A protein is considered as a term string composed by gapped-dipeptides, which are defined as any two residues separated by one or m …
We present PSLDoc, a method based on gapped-dipeptides and probabilistic latent semantic analysis (PLSA) to solve this problem. A
Lipid exposure prediction enhances the inference of rotational angles of transmembrane helices.
Lai JS, Cheng CW, Lo A, Sung TY, Hsu WL. Lai JS, et al. Among authors: lo a. BMC Bioinformatics. 2013 Oct 11;14:304. doi: 10.1186/1471-2105-14-304. BMC Bioinformatics. 2013. PMID: 24112406 Free PMC article.
The rotational angle of a transmembrane helix is related to the exposed surface of a transmembrane helix, since lipid exposure gives the degree of accessibility of each residue in lipid environment. ...When rotational angles can be accurately predicted, free modelin …
The rotational angle of a transmembrane helix is related to the exposed surface of a transmembrane helix, since lipid exposure …
TMPad: an integrated structural database for helix-packing folds in transmembrane proteins.
Lo A, Cheng CW, Chiu YY, Sung TY, Hsu WL. Lo A, et al. Nucleic Acids Res. 2011 Jan;39(Database issue):D347-55. doi: 10.1093/nar/gkq1255. Nucleic Acids Res. 2011. PMID: 21177659 Free PMC article.
However, such information is difficult to obtain because of the experimental impediment and a lack of a well-annotated source of helix-packing folds in TM proteins. ...
However, such information is difficult to obtain because of the experimental impediment and a lack of a well-annotated source …
Predicting helix-helix interactions from residue contacts in membrane proteins.
Lo A, Chiu YY, Rødland EA, Lyu PC, Sung TY, Hsu WL. Lo A, et al. Bioinformatics. 2009 Apr 15;25(8):996-1003. doi: 10.1093/bioinformatics/btp114. Epub 2009 Feb 25. Bioinformatics. 2009. PMID: 19244388 Free PMC article.
MOTIVATION: Helix-helix interactions play a critical role in the structure assembly, stability and function of membrane proteins. ...Our results demonstrate that a hierarchical framework can be applied to eliminate false positives (FP) while reducing computational c …
MOTIVATION: Helix-helix interactions play a critical role in the structure assembly, stability and function of membrane proteins. ... …
Enhanced membrane protein topology prediction using a hierarchical classification method and a new scoring function.
Lo A, Chiu HS, Sung TY, Lyu PC, Hsu WL. Lo A, et al. J Proteome Res. 2008 Feb;7(2):487-96. doi: 10.1021/pr0702058. J Proteome Res. 2008. PMID: 18081245
The prediction of transmembrane (TM) helix and topology provides important information about the structure and function of a membrane protein. Due to the experimental difficulties in obtaining a high-resolution model, computational methods are highly desirable. In t …
The prediction of transmembrane (TM) helix and topology provides important information about the structure and function of a membrane …
Protein subcellular localization prediction based on compartment-specific features and structure conservation.
Su EC, Chiu HS, Lo A, Hwang JK, Sung TY, Hsu WL. Su EC, et al. Among authors: lo a. BMC Bioinformatics. 2007 Sep 8;8:330. doi: 10.1186/1471-2105-8-330. BMC Bioinformatics. 2007. PMID: 17825110 Free PMC article.
RESULTS: We propose a hybrid prediction method for Gram-negative bacteria that combines a one-versus-one support vector machines (SVM) model and a structural homology approach. ...CONCLUSION: Our results demonstrate that biological features derived from Gram- …
RESULTS: We propose a hybrid prediction method for Gram-negative bacteria that combines a one-versus-one support vector machin …
Transmembrane helix and topology prediction using hierarchical SVM classifiers and an alternating geometric scoring function.
Lo A, Chiu HS, Sung TY, Hsu WL. Lo A, et al. Comput Syst Bioinformatics Conf. 2006:31-42. Comput Syst Bioinformatics Conf. 2006. PMID: 17369623
MOTIVATION: A key class of membrane proteins contains one or more transmembrane (TM) helices, traversing the membrane lipid bilayer. ...RESULTS: We develop a method based on support vector machines (SVM) in a hierarchical framework to predict TM helices first …
MOTIVATION: A key class of membrane proteins contains one or more transmembrane (TM) helices, traversing the membrane lipid bilayer. …
Protein subcellular localization prediction based on compartment-specific biological features.
Su CY, Lo A, Chiu HS, Sung TY, Hsu WL. Su CY, et al. Among authors: lo a. Comput Syst Bioinformatics Conf. 2006:325-30. Comput Syst Bioinformatics Conf. 2006. PMID: 17369650
The final prediction of localization sites is determined by integrating the results from ten binary classifiers using a combination of majority votes and a probabilistic method. The overall accuracy reaches 91.4%, which is 1.6% better than the state-of-the-art syste …
The final prediction of localization sites is determined by integrating the results from ten binary classifiers using a combination o …
Long term toxicity of intracranial germ cell tumor treatment in adolescents and young adults.
Wong J, Goddard K, Laperriere N, Dang J, Bouffet E, Bartels U, Hodgson D, Tyldesley S, Hukin J, Cheng S, Bedard PL, Lo AC. Wong J, et al. Among authors: lo ac. J Neurooncol. 2020 Oct 9. doi: 10.1007/s11060-020-03642-1. Online ahead of print. J Neurooncol. 2020. PMID: 33034840
Novel Programmed Cell Death as Therapeutic Targets in Age-Related Macular Degeneration?
Yang M, So KF, Lam WC, Lo ACY. Yang M, et al. Among authors: lo acy. Int J Mol Sci. 2020 Oct 1;21(19):E7279. doi: 10.3390/ijms21197279. Int J Mol Sci. 2020. PMID: 33019767 Free article. Review.
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