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Author

Jian Zhou

Bio: Jian Zhou is an academic researcher from Chongqing University. The author has contributed to research in topic(s): Hepatocellular carcinoma & Enantioselective synthesis. The author has an hindex of 128, co-authored 3007 publication(s) receiving 91402 citation(s). Previous affiliations of Jian Zhou include Minzu University of China & Max Planck Society.
Papers
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Journal ArticleDOI
Jian Zhou1, Olga G. Troyanskaya1Institutions (1)
TL;DR: A deep learning–based algorithmic framework, DeepSEA, is developed that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity and improving prioritization of functional variants.
Abstract: Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.

1,323 citations


Journal ArticleDOI
Jun Kang, Sefaattin Tongay1, Jian Zhou1, Jingbo Li  +2 moreInstitutions (2)
Abstract: The band offsets and heterostructures of monolayer and few-layer transition-metal dichalcogenides MX2 (M = Mo, W; X = S, Se, Te) are investigated from first principles calculations. The band alignments between different MX2 monolayers are calculated using the vacuum level as reference, and a simple model is proposed to explain the observed chemical trends. Some of the monolayers and their heterostructures show band alignments suitable for potential applications in spontaneous water splitting, photovoltaics, and optoelectronics. The strong dependence of the band offset on the number of layers also implicates a possible way of patterning quantum structures with thickness engineering.

1,204 citations


Journal ArticleDOI
Sefaattin Tongay1, Jian Zhou1, Can Ataca2, Kelvin Lo1  +5 moreInstitutions (4)
TL;DR: It is demonstrated that, in a few-layer sample where the indirect bandgap and direct bandgap are nearly degenerate, the temperature rise can effectively drive the system toward the 2D limit by thermally decoupling neighboring layers via interlayer thermal expansion.
Abstract: Layered semiconductors based on transition-metal chalcogenides usually cross from indirect bandgap in the bulk limit over to direct bandgap in the quantum (2D) limit. Such a crossover can be achieved by peeling off a multilayer sample to a single layer. For exploration of physical behavior and device applications, it is much desired to reversibly modulate such crossover in a multilayer sample. Here we demonstrate that, in a few-layer sample where the indirect bandgap and direct bandgap are nearly degenerate, the temperature rise can effectively drive the system toward the 2D limit by thermally decoupling neighboring layers via interlayer thermal expansion. Such a situation is realized in few-layer MoSe2, which shows stark contrast from the well-explored MoS2 where the indirect and direct bandgaps are far from degenerate. Photoluminescence of few-layer MoSe2 is much enhanced with the temperature rise, much like the way that the photoluminescence is enhanced due to the bandgap crossover going from the bulk to the quantum limit, offering potential applications involving external modulation of optical properties in 2D semiconductors. The direct bandgap of MoSe2, identified at 1.55 eV, may also promise applications in energy conversion involving solar spectrum, as it is close to the optimal bandgap value of single-junction solar cells and photoelechemical devices.

1,029 citations


Journal ArticleDOI
Abstract: The 3,3′-disubstituted oxindole structural motif is a prominent feature in many alkaloid natural products, which include all kinds of tetrasubstituted carbon stereocenters, spirocyclic or not, all-carbon or heteroatom-containing. The catalytic asymmetric synthesis of the tetrasubstituted carbon stereocenter at the C-3 position of the oxindole framework integrates new synthetic methods and chiral catalysts, reflects the latest achievements in asymmetric catalysis, and facilitates the synthesis of sufficient quantities of related compounds as potential medicinal agents and biological probes. This review summarizes the recent progress in this area, and applications in the total synthesis of related bioactive compounds.

1,015 citations


Journal ArticleDOI
Qiang Gao1, Shuang-Jian Qiu1, Jia Fan1, Jian Zhou1  +5 moreInstitutions (1)
TL;DR: Tregs are associated with HCC invasiveness, and intratumoral balance of regulatory and cytotoxic T cells is a promising independent predictor for recurrence and survival in HCC.
Abstract: Purpose To investigate the prognostic value of tumor-infiltrating lymphocytes (TILs), especially regulatory T cells (Tregs), in hepatocellular carcinoma (HCC) patients after resection. Patients and Methods CD3+, CD4+, CD8+, Foxp3-positive, and granzyme B-positive TILs were assessed by immunohistochemistry in tissue microarrays containing HCC from 302 patients. Prognostic effects of low- or high-density TIL subsets were evaluated by Cox regression and Kaplan-Meier analysis using median values as cutoff. Results CD3+, CD4+, CD8+ TILs were associated with neither overall survival (OS) nor disease-free survival (DFS). The presence of low intratumoral Tregs in combination with high intratumoral activated CD8+ cytotoxic cells (CTLs), a balance toward CTLs, was an independent prognostic factor for both improved DFS (P = .001) and OS (P < .0001). Five-year OS and DFS rates were only 24.1% and 19.8% for the group with intratumoral high Tregs and low activated CTLs, compared with 64.0% and 59.4% for the group with ...

921 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

30,199 citations



Book
18 Nov 2016
Abstract: Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

26,972 citations


Steven J. Plimpton1Institutions (1)
01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

24,496 citations


28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations


Network Information
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Performance
Metrics

Author's H-index: 128

No. of papers from the Author in previous years
YearPapers
202213
2021338
2020333
2019260
2018228
2017230