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Tao Huang

Researcher at Chinese Academy of Sciences

Publications -  325
Citations -  12593

Tao Huang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 41, co-authored 248 publications receiving 10196 citations. Previous affiliations of Tao Huang include CAS-MPG Partner Institute for Computational Biology & Shanghai Mental Health Center.

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Immunosignature Screening for Multiple Cancer Subtypes Based on Expression Rule

TL;DR: This study reused two sets of peptide microarray data that detected the expression level of potential antigenic peptides derived from tumor tissues to avoid the detection differences induced by chip platforms and extracted quantitative rules for accurate cancer immune monitoring and pathologic diagnosis.
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Using WPNNA Classifier in Ubiquitination Site Prediction Based on Hybrid Features

TL;DR: A new classifier called weighted passive nearest neighbor algorithm (WPNNA) is applied to predict the ubiquitination sites using a hybrid of features, including PSSM conservation scores, amino acid factors and disorder scores, which indicates that the predictor based on WPNNA is as least a good complement to the current state of art in ubiquitinations site prediction.
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Smoking Status and Type 2 Diabetes, and Cardiovascular Disease: A Comprehensive Analysis of Shared Genetic Etiology and Causal Relationship

TL;DR: The findings provide strong evidence on shared genetic etiology and causal associations between smoking status and T2D, CAD, MI, and HF, underscoring the potential shared biological mechanisms underlying the link between smoking and T1D and CVDs.
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Mutation profile and associated clinical features in Chinese patients with cytogenetically normal acute myeloid leukemia

TL;DR: Cytogenetically normal acute myeloid leukemia (CN‐AML), which accounted for nearly half of total AML patients, is a highly heterogeneous subset of AML.
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Identifying the RNA signatures of coronary artery disease from combined lncRNA and mRNA expression profiles.

TL;DR: In this study, a computational analysis was conducted on patients with CAD by using a comprehensive transcription dataset with combined mRNA and lncRNA expression data to help understand mRNA andLNCRNA expression levels in CAD.