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ORCIDXiaotong Lin 0001
Person information
- affiliation: Oakland University, Department of Computer Science and Engineering, Rochester, MI, USA
- affiliation (PhD 2012): University of Kansas, Bioinformatics and Computational Life-Science Laboratory, Lawrence, KS, USA
Other persons with the same name
- Xiaotong Lin — disambiguation page
- Xiaotong Lin 0002
![[0009-0009-3012-1253]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0009-0009-3012-1253")
— Sun Yat-sen University (SYSU), Guangzhou, China - Xiaotong Lin 0003 — Guangzhou University, School of Mathematics and Information Science, Guangzhou, China
- Xiaotong Lin 0004 — Agere Systems, Allentown, PA, USA (and 1 more)
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Books and Theses
- 2012
[b1]Xiaotong Lin:
Bayesian network learning and applications in Bioinformatics. University of Kansas, USA, 2012
Journal Articles
- 2014
- [j4]Xue-wen Chen, Xiaotong Lin:
Big Data Deep Learning: Challenges and Perspectives. IEEE Access 2: 514-525 (2014) - 2011
- [j3]Jong Cheol Jeong, Xiaotong Lin, Xue-wen Chen:
On Position-Specific Scoring Matrix for Protein Function Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 8(2): 308-315 (2011) - 2009
- [j2]Xiaotong Lin, Mei Liu, Xue-wen Chen:
Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms. BMC Bioinform. 10(S-4) (2009) - 2008
- [j1]Xue-wen Chen, Gopalakrishna Anantha, Xiaotong Lin:
Improving Bayesian Network Structure Learning with Mutual Information-Based Node Ordering in the K2 Algorithm. IEEE Trans. Knowl. Data Eng. 20(5): 628-640 (2008)
Conference and Workshop Papers
- 2010
- [c4]Xiaotong Lin, Xue-wen Chen:
Mr.KNN: soft relevance for multi-label classification. CIKM 2010: 349-358 - 2009
- [c3]Xue-wen Chen, Haixun Wang, Xiaotong Lin:
Learning to rank with a novel kernel perceptron method. CIKM 2009: 505-512 - 2008
- [c2]Xiaotong Lin, Mei Liu, Xue-wen Chen:
Protein-Protein Interaction Prediction and Assessment from Model Organisms. BIBM 2008: 187-192 - [c1]Xiaotong Lin, Xue-wen Chen:
Gene Network Learning Using Regulated Dynamic Bayesian Network Methods. ICMLA 2008: 717-722
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