个人介绍

Self-introduction

尤著宏,博士,中科院新疆理化技术研究所研究员、中国科学院大学博士生导师,中科院率先行动“百人计划”青年俊才候选人、国家自然科学基金委优秀青年科学基金获得者、第十四批国家千人计划-新疆项目入选者。2010年12月于中国科学技术大学获工学博士学位;2008年6月-2009年12月,美国康奈尔大学联合培养博士生;2012年起,在同济大学计算机科学与技术博士后流动站从事博士后研究;2013年获人社部“香江学者”计划资助,在香港理工大学电子计算学系从事博士后研究,合作导师Prof. Keith C.C. Chan。

主要从事模式识别理论及生物信息数据挖掘研究,主要工作集中在利用复杂网络、模式识别、深度学习、数据挖掘等方法对蛋白质组学、非编码RNA和药物靶标发现等生物信息学领域的多个重要问题进行探索和研究,并取得一系列重要进展:(1)针对复杂生物信息数据具有的海量、高维、高冗余、高噪声等特性,提出了一套完整表征生物数据的特征建模、特征提取及维数约简新理论、新方法,为后续高效模式识别理论的设计奠定了基础;(2)建立了以复杂网络分析为核心的高效学习理论,使之能更好地处理多模态、动态、分层及关联的复杂生物数据;(3)提出一系列基于智能计算的复杂生物数据高效学习算法,为系统生物学中相关领域的研究及发展提供科学的辅助手段和工具。尤博士目前研究方向包括药物靶点预测、蛋白质相互作用预测、microRNA与疾病关系预测、lncRNA与疾病关系研究、疾病-微生物关联预测研究、药物组合研究等。这些研究方向是近年来计算机科学和生命科学等诸多领域交叉研究的前沿和热点,具有重要的理论意义和实际价值。

发表论文

Published Papers
1 Efficient Framework for Predicting ncRNA-Protein Interactions Based on Sequence Information by Deep Learning.SCI.

2 Discovering an Integrated Network in Heterogeneous Data for Predicting lncRNA-miRNA Interactions.SCI.

3 Using Weighted Extreme Learning Machine Combined with Scale-Invariant Feature Transform to Predict Protein-Protein Interactions from Protein Evolutionary Information.SCI.

4 RP-FIRF: Prediction of Self-interacting Proteins Using Random Projection Classifier Combining with Finite Impulse Response Filter.SCI.

5 Prediction of Protein Self-Interactions using Stacked Long Short-Term Memory from Protein Sequences Information.SCI.

6 DRMDA: Deep Representations-based MiRNA-Disease Association prediction.SCI.

7 Efficient Framework for Predicting ncRNA-Protein Interactions Based on Sequence Information by Deep Learning.CI.

8 Improving Prediction of Self-interacting Proteins Using Stacked Sparse Auto-Encoder with PSSM profiles.SCI.

9 Accurate Prediction of ncRNA-Protein Interactions From the Integration of Sequence and Evolutionary Information.SCI.

10 Predicting Protein Interactions Using a Deep Learning Method Combined Stacked Sparse Autoencoder with Probabilistic Classification Vector Machine.SCI.

11 DroidDet: effective and robust detection of Android malware using static analysis along with rotation forest model.SCI.

12 An Ensemble Classifier with Random Projection for Predicting Protein–Protein Interactions Using Sequence and Evolutionary Information.SCI.

13 A Computational-Based Method for Predicting Drug–Target Interactions by Using Stacked Autoencoder Deep Neural Network.SCI.

14 PCLPred:A Bioinformatics Method for Predicting Protein-Protein Interactions by Combining Relevance Vector Machine Model with Low-Rank Matrix Approximation.SCI.

15 Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data.SCI.

16 BNPMDA: Bipartite Network Projection for MiRNA-Disease Association prediction.SCI.

17 RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions using Drug Structure and Protein Sequence Information.SCI.

18 A Systematic Prediction of Drug-Target Interactions using Molecular Fingerprints and Protein Sequences.SCI.

19 An improved efficient rotation forest algorithm to predict the interactions among proteins.SCI.

20 A Deep Learning Framework for Robust and Accurate prediction of ncRNA-Protein Interactions using Evolutionary Information.SCI.

社会兼职

Social Appointments
尤博士目前是IEEE会员和中国计算机学会CCF计算机应用专委会常委。担任Journal of Biological Research、International Journal of Distributed Sensor Networks、Evolutionary Bioinformatics、Current Topics in Medicinal Chemistry及BioMed Research International 5个SCI国际期刊的客座编委(Guest Editor)以及Current Proteomics期刊编辑顾问委员会(Editorial Advisory Board)委员和地区编辑Regional Editor,是多个IEEE Transactions汇刊及高水平SCI国际期刊特邀审稿人。