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Items: 1 to 20 of 4405

1.

CMEP: a database for circulating microRNA expression profiling.

Li JR, Tong CY, Sung TJ, Kang TY, Zhou XJ, Liu CC.

Bioinformatics. 2019 Jan 22. doi: 10.1093/bioinformatics/btz042. [Epub ahead of print]

PMID:
30668638
2.

Integrating life history traits into predictive phylogeography.

Sullivan J, Smith ML, Espíndola A, Ruffley M, Rankin A, Tank D, Carstens B.

Mol Ecol. 2019 Jan 22. doi: 10.1111/mec.15029. [Epub ahead of print]

PMID:
30667113
3.

Identifying lupus patients in electronic health records: Development and validation of machine learning algorithms and application of rule-based algorithms.

Jorge A, Castro VM, Barnado A, Gainer V, Hong C, Cai T, Cai T, Carroll R, Denny JC, Crofford L, Costenbader KH, Liao KP, Karlson EW, Feldman CH.

Semin Arthritis Rheum. 2019 Jan 4. pii: S0049-0172(18)30651-6. doi: 10.1016/j.semarthrit.2019.01.002. [Epub ahead of print]

PMID:
30665626
4.

Principal component analysis of binary genomics data.

Song Y, Westerhuis JA, Aben N, Michaut M, Wessels LFA, Smilde AK.

Brief Bioinform. 2019 Jan 18;20(1):317-329. doi: 10.1093/bib/bbx119.

PMID:
30657888
5.

Leveraging Human Genetics to Guide Cancer Drug Development.

Kinnersley B, Sud A, Coker EA, Tym JE, Di Micco P, Al-Lazikani B, Houlston RS.

JCO Clin Cancer Inform. 2018 Dec;(2):1-11. doi: 10.1200/CCI.18.00077.

6.

Automated Renal Cancer Grading Using Nuclear Pleomorphic Patterns.

Holdbrook DA, Singh M, Choudhury Y, Kalaw EM, Koh V, Tan HS, Kanesvaran R, Tan PH, Peng JYS, Tan MH, Lee HK.

JCO Clin Cancer Inform. 2018 Dec;(2):1-12. doi: 10.1200/CCI.17.00100.

7.

A unifying framework for interpreting and predicting mutualistic systems.

Wu F, Lopatkin AJ, Needs DA, Lee CT, Mukherjee S, You L.

Nat Commun. 2019 Jan 16;10(1):242. doi: 10.1038/s41467-018-08188-5.

8.

SMuRF: Portable and accurate ensemble prediction of somatic mutations.

Huang W, Guo YA, Muthukumar K, Baruah P, Chang MM, Skanderup AJ.

Bioinformatics. 2019 Jan 12. doi: 10.1093/bioinformatics/btz018. [Epub ahead of print]

PMID:
30649191
9.

A Simple Convolutional Neural Network for Prediction of Enhancer-Promoter Interactions with DNA Sequence Data.

Zhuang Z, Shen X, Pan W.

Bioinformatics. 2019 Jan 14. doi: 10.1093/bioinformatics/bty1050. [Epub ahead of print]

PMID:
30649185
10.

Value of Neighborhood Socioeconomic Status in Predicting Risk of Outcomes in Studies That Use Electronic Health Record Data.

Bhavsar NA, Gao A, Phelan M, Pagidipati NJ, Goldstein BA.

JAMA Netw Open. 2018 Sep 7;1(5):e182716. doi: 10.1001/jamanetworkopen.2018.2716.

PMID:
30646172
11.

Subject Matter Knowledge in the Age of Big Data and Machine Learning.

Goldstein BA, Carlson D, Bhavsar NA.

JAMA Netw Open. 2018 Aug 3;1(4):e181568. doi: 10.1001/jamanetworkopen.2018.1568. No abstract available.

PMID:
30646126
12.

High-Throughput Omics and Statistical Learning Integration for the Discovery and Validation of Novel Diagnostic Signatures in Colorectal Cancer.

Long NP, Park S, Anh NH, Nghi TD, Yoon SJ, Park JH, Lim J, Kwon SW.

Int J Mol Sci. 2019 Jan 12;20(2). pii: E296. doi: 10.3390/ijms20020296.

13.

Integration of A Deep Learning Classifier with A Random Forest Approach for Predicting Malonylation Sites.

Chen Z, He N, Huang Y, Qin WT, Liu X, Li L.

Genomics Proteomics Bioinformatics. 2019 Jan 10. pii: S1672-0229(19)30002-6. doi: 10.1016/j.gpb.2018.08.004. [Epub ahead of print]

14.

Increasing workflow development speed and reproducibility with Vectools.

Weirick T, Müller R, Uchida S.

Version 2. F1000Res. 2018 Sep 20 [revised 2018 Jan 1];7:1499. doi: 10.12688/f1000research.16301.2. eCollection 2018.

15.

Computational Resources for Prediction and Analysis of Functional miRNA and Their Targetome.

Monga I, Kumar M.

Methods Mol Biol. 2019;1912:215-250. doi: 10.1007/978-1-4939-8982-9_9.

PMID:
30635896
16.

Workflow Development for the Functional Characterization of ncRNAs.

Wolfien M, Brauer DL, Bagnacani A, Wolkenhauer O.

Methods Mol Biol. 2019;1912:111-132. doi: 10.1007/978-1-4939-8982-9_5.

PMID:
30635892
17.

Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine.

Ghosh D, Bernstein JA, Khurana Hershey GK, Rothenberg ME, Mersha TB.

Front Immunol. 2018 Dec 12;9:2727. doi: 10.3389/fimmu.2018.02727. eCollection 2018. Review.

18.

Investigating the role of Simpson's paradox in the analysis of top-ranked features in high-dimensional bioinformatics datasets.

Freitas AA.

Brief Bioinform. 2019 Jan 9. doi: 10.1093/bib/bby126. [Epub ahead of print]

PMID:
30629111
19.

A review on machine learning methods for in silico toxicity prediction.

Idakwo G, Luttrell J, Chen M, Hong H, Zhou Z, Gong P, Zhang C.

J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2019 Jan 10:1-23. doi: 10.1080/10590501.2018.1537118. [Epub ahead of print]

PMID:
30628866
20.

A model to predict the function of hypothetical proteins through a nine-point classification scoring schema.

Ijaq J, Malik G, Kumar A, Das PS, Meena N, Bethi N, Sundararajan VS, Suravajhala P.

BMC Bioinformatics. 2019 Jan 8;20(1):14. doi: 10.1186/s12859-018-2554-y.

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