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A statistical reappraisal of the findings of an esophageal cancer genome-wide association study.
Statnikov A, Li C, Aliferis CF. Statnikov A, et al. Cancer Res. 2008 Apr 15;68(8):3074-5; author reply 3075. doi: 10.1158/0008-5472.CAN-07-2999. Cancer Res. 2008. PMID: 18413779 No abstract available.
Effects of environment, genetics and data analysis pitfalls in an esophageal cancer genome-wide association study.
Statnikov A, Li C, Aliferis CF. Statnikov A, et al. PLoS One. 2007 Sep 26;2(9):e958. doi: 10.1371/journal.pone.0000958. PLoS One. 2007. PMID: 17895998 Free PMC article.
METHODOLOGY/PRINCIPAL FINDINGS: In the present paper we undertake a careful examination of the relative significance of genetics, environmental factors, and biases of the data analysis protocol that was used in a previously published genome-wide association study. . …
METHODOLOGY/PRINCIPAL FINDINGS: In the present paper we undertake a careful examination of the relative significance of genetics, env …
Factors influencing the statistical power of complex data analysis protocols for molecular signature development from microarray data.
Aliferis CF, Statnikov A, Tsamardinos I, Schildcrout JS, Shepherd BE, Harrell FE Jr. Aliferis CF, et al. Among authors: statnikov a. PLoS One. 2009;4(3):e4922. doi: 10.1371/journal.pone.0004922. Epub 2009 Mar 17. PLoS One. 2009. PMID: 19290050 Free PMC article.
Challenges in the analysis of mass-throughput data: a technical commentary from the statistical machine learning perspective.
Aliferis CF, Statnikov A, Tsamardinos I. Aliferis CF, et al. Among authors: statnikov a. Cancer Inform. 2007 Feb 16;2:133-62. Cancer Inform. 2007. PMID: 19458765 Free PMC article.
The novel nature and high-dimensionality in such datasets pose a series of nontrivial data analysis problems. This technical commentary discusses the problems of over-fitting, error estimation, curse of dimensionality, causal versus predictive modeling, integration of hete …
The novel nature and high-dimensionality in such datasets pose a series of nontrivial data analysis problems. This technical commenta …
The FAST-AIMS Clinical Mass Spectrometry Analysis System.
Fananapazir N, Statnikov A, Aliferis CF. Fananapazir N, et al. Among authors: statnikov a. Adv Bioinformatics. 2009;2009:598241. doi: 10.1155/2009/598241. Epub 2009 Jul 9. Adv Bioinformatics. 2009. PMID: 19956420 Free PMC article.
We have designed and implemented a stand-alone software system, FAST-AIMS, which seeks to meet this need through automation of data preprocessing, feature selection, classification model generation, and performance estimation. ...
We have designed and implemented a stand-alone software system, FAST-AIMS, which seeks to meet this need through automation of data p …
Causal graph-based analysis of genome-wide association data in rheumatoid arthritis.
Alekseyenko AV, Lytkin NI, Ai J, Ding B, Padyukov L, Aliferis CF, Statnikov A. Alekseyenko AV, et al. Among authors: statnikov a. Biol Direct. 2011 May 18;6:25. doi: 10.1186/1745-6150-6-25. Biol Direct. 2011. PMID: 21592391 Free PMC article.
BACKGROUND: GWAS owe their popularity to the expectation that they will make a major impact on diagnosis, prognosis and management of disease by uncovering genetics underlying clinical phenotypes. ...Recent advances in other genomics domains pinpoint multivariate causal gr …
BACKGROUND: GWAS owe their popularity to the expectation that they will make a major impact on diagnosis, prognosis and management of …
Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD.
Galatzer-Levy IR, Ma S, Statnikov A, Yehuda R, Shalev AY. Galatzer-Levy IR, et al. Among authors: statnikov a. Transl Psychiatry. 2017 Mar 21;7(3):e0. doi: 10.1038/tp.2017.38. Transl Psychiatry. 2017. PMID: 28323285 Free PMC article.
Are random forests better than support vector machines for microarray-based cancer classification?
Statnikov A, Aliferis CF. Statnikov A, et al. AMIA Annu Symp Proc. 2007 Oct 11;2007:686-90. AMIA Annu Symp Proc. 2007. PMID: 18693924 Free PMC article.
In the present paper we point to several biases of this prior work and conduct a new unbiased evaluation of the two algorithms. Our experiments using 18 diagnostic and prognostic datasets show that support vector machines outperform random forests often by a large m …
In the present paper we point to several biases of this prior work and conduct a new unbiased evaluation of the two algorithms. Our e …
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification.
Statnikov A, Wang L, Aliferis CF. Statnikov A, et al. BMC Bioinformatics. 2008 Jul 22;9:319. doi: 10.1186/1471-2105-9-319. BMC Bioinformatics. 2008. PMID: 18647401 Free PMC article.
As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. ...Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random fo …
As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classifi …
Extracting drug-drug interaction articles from MEDLINE to improve the content of drug databases.
Duda S, Aliferis C, Miller R, Statnikov A, Johnson K. Duda S, et al. Among authors: statnikov a. AMIA Annu Symp Proc. 2005;2005:216-20. AMIA Annu Symp Proc. 2005. PMID: 16779033 Free PMC article.
MEDLINE represents a respected source of peer-reviewed biomedical citations that potentially might serve as a valuable source of drug-drug interaction information, if relevant articles could be pinpointed effectively and efficiently. We evaluated the classification …
MEDLINE represents a respected source of peer-reviewed biomedical citations that potentially might serve as a valuable source …
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