yifeng yang - Academia.edu (original) (raw)
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Papers by yifeng yang
Neuroscience Letters, 2004
Background: Schizophrenia is a chronic psychiatric disorder with a strong genetic component. Seve... more Background: Schizophrenia is a chronic psychiatric disorder with a strong genetic component. Several studies have suggested that dysfunctions in the glutamatergic transmission are linked to the pathogenesis of schizophrenia, and that the kainate ionotropic glutamate receptors are involved in this mechanism. A recent study provides cytogenetic and genetic evidence to support a role for the kainate-type glutamate receptor gene (GRIK4), in schizophrenia. A systematic case-control association study of GRIK4 involving a Scottish population found that three SNPs, rs4935752, rs6589846 and rs4430518, were associated with schizophrenia. Methods: Here, we investigated rs4935752, rs6589846, rs4430518 and other 2 SNPs within the GRIK4 gene in an association study of the Chinese population. Our sample consisted of 288 schizophrenia and 288 control subjects. All recruits were Han Chinese drawn from the city of Shanghai. Results: No individual SNP nor any haplotype was associated with schizophrenia in our study. Conclusion: These results suggest that the five SNPs within the GRIK4 gene are unlikely to play a major role in the susceptibility to schizophrenia in the Chinese population.
BMC Bioinformatics, 2006
Background Understanding gene regulatory networks has become one of the central research problems... more Background Understanding gene regulatory networks has become one of the central research problems in bioinformatics. More than thirty algorithms have been proposed to identify DNA regulatory sites during the past thirty years. However, the prediction accuracy of these algorithms is still quite low. Ensemble algorithms have emerged as an effective strategy in bioinformatics for improving the prediction accuracy by exploiting the synergetic prediction capability of multiple algorithms. Results We proposed a novel clustering-based ensemble algorithm named EMD forde novomotif discovery by combining multiple predictions from multiple runs of one or more base component algorithms. The ensemble approach is applied to the motif discovery problem for the first time. The algorithm is tested on a benchmark dataset generated fromE. coliRegulonDB. The EMD algorithm has achieved 22.4% improvement in terms of the nucleotide level prediction accuracy over the best stand-alone component algorithm. The advantage of the EMD algorithm is more significant for shorter input sequences, but most importantly, it always outperforms or at least stays at the same performance level of the stand-alone component algorithms even for longer sequences. Conclusion We proposed an ensemble approach for the motif discovery problem by taking advantage of the availability of a large number of motif discovery programs. We have shown that the ensemble approach is an effective strategy for improving both sensitivity and specificity, thus the accuracy of the prediction. The advantage of the EMD algorithm is its flexibility in the sense that a new powerful algorithm can be easily added to the system.
Neuroscience Letters, 2004
Background: Schizophrenia is a chronic psychiatric disorder with a strong genetic component. Seve... more Background: Schizophrenia is a chronic psychiatric disorder with a strong genetic component. Several studies have suggested that dysfunctions in the glutamatergic transmission are linked to the pathogenesis of schizophrenia, and that the kainate ionotropic glutamate receptors are involved in this mechanism. A recent study provides cytogenetic and genetic evidence to support a role for the kainate-type glutamate receptor gene (GRIK4), in schizophrenia. A systematic case-control association study of GRIK4 involving a Scottish population found that three SNPs, rs4935752, rs6589846 and rs4430518, were associated with schizophrenia. Methods: Here, we investigated rs4935752, rs6589846, rs4430518 and other 2 SNPs within the GRIK4 gene in an association study of the Chinese population. Our sample consisted of 288 schizophrenia and 288 control subjects. All recruits were Han Chinese drawn from the city of Shanghai. Results: No individual SNP nor any haplotype was associated with schizophrenia in our study. Conclusion: These results suggest that the five SNPs within the GRIK4 gene are unlikely to play a major role in the susceptibility to schizophrenia in the Chinese population.
BMC Bioinformatics, 2006
Background Understanding gene regulatory networks has become one of the central research problems... more Background Understanding gene regulatory networks has become one of the central research problems in bioinformatics. More than thirty algorithms have been proposed to identify DNA regulatory sites during the past thirty years. However, the prediction accuracy of these algorithms is still quite low. Ensemble algorithms have emerged as an effective strategy in bioinformatics for improving the prediction accuracy by exploiting the synergetic prediction capability of multiple algorithms. Results We proposed a novel clustering-based ensemble algorithm named EMD forde novomotif discovery by combining multiple predictions from multiple runs of one or more base component algorithms. The ensemble approach is applied to the motif discovery problem for the first time. The algorithm is tested on a benchmark dataset generated fromE. coliRegulonDB. The EMD algorithm has achieved 22.4% improvement in terms of the nucleotide level prediction accuracy over the best stand-alone component algorithm. The advantage of the EMD algorithm is more significant for shorter input sequences, but most importantly, it always outperforms or at least stays at the same performance level of the stand-alone component algorithms even for longer sequences. Conclusion We proposed an ensemble approach for the motif discovery problem by taking advantage of the availability of a large number of motif discovery programs. We have shown that the ensemble approach is an effective strategy for improving both sensitivity and specificity, thus the accuracy of the prediction. The advantage of the EMD algorithm is its flexibility in the sense that a new powerful algorithm can be easily added to the system.