Tongji University

About: Tongji University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Computer science & Population. The organization has 76116 authors who have published 81176 publications receiving 1248911 citations. The organization is also known as: Tongji & Tóngjì Dàxué.

Target analysis by integration of transcriptome and ChIP-seq data with BETA

Abstract: The combination of ChIP-seq and transcriptome analysis is a compelling approach to unravel the regulation of gene expression. Several recently published methods combine transcription factor (TF) binding and gene expression for target prediction, but few of them provide an efficient software package for the community. Binding and expression target analysis (BETA) is a software package that integrates ChIP-seq of TFs or chromatin regulators with differential gene expression data to infer direct target genes. BETA has three functions: (i) to predict whether the factor has activating or repressive function; (ii) to infer the factor's target genes; and (iii) to identify the motif of the factor and its collaborators, which might modulate the factor's activating or repressive function. Here we describe the implementation and features of BETA to demonstrate its application to several data sets. BETA requires ~1 GB of RAM, and the procedure takes 20 min to complete. BETA is available open source at http://cistrome.org/BETA/.

A review: Knowledge reasoning over knowledge graph

Abstract: Mining valuable hidden knowledge from large-scale data relies on the support of reasoning technology. Knowledge graphs, as a new type of knowledge representation, have gained much attention in natural language processing. Knowledge graphs can effectively organize and represent knowledge so that it can be efficiently utilized in advanced applications. Recently, reasoning over knowledge graphs has become a hot research topic, since it can obtain new knowledge and conclusions from existing data. Herein we review the basic concept and definitions of knowledge reasoning and the methods for reasoning over knowledge graphs. Specifically, we dissect the reasoning methods into three categories: rule-based reasoning, distributed representation-based reasoning and neural network-based reasoning. We also review the related applications of knowledge graph reasoning, such as knowledge graph completion, question answering, and recommender systems. Finally, we discuss the remaining challenges and research opportunities for knowledge graph reasoning.

Reversible multi-electron redox chemistry of π-conjugated N-containing heteroaromatic molecule-based organic cathodes

Abstract: Even though organic molecules with well-designed functional groups can be programmed to have high electron density per unit mass, their poor electrical conductivity and low cycle stability limit their applications in batteries. Here we report a facile synthesis of π-conjugated quinoxaline-based heteroaromatic molecules (3Q) by condensation of cyclic carbonyl molecules with o-phenylenediamine. 3Q features a number of electron-deficient pyrazine sites, where multiple redox reactions take place. When hybridized with graphene and coupled with an ether-based electrolyte, an organic cathode based on 3Q molecules displays a discharge capacity of 395 mAh g−1 at 400 mA g−1 (1C) in the voltage range of 1.2–3.9 V and a nearly 70% capacity retention after 10,000 cycles at 8 A g−1. It also exhibits a capacity of 222 mAh g−1 at 20C, which corresponds to 60% of the initial specific capacity. Our results offer evidence that heteroaromatic molecules with multiple redox sites are promising in developing high-energy-density, long-cycle-life organic rechargeable batteries. Organic compounds can be used as electrode materials for Li-ion batteries, but problems such as facile dissolution and low electrical conductivity hinder their application. Here the authors report π-conjugated quinoxaline-based heteroaromatic molecules with multiple redox sites to tackle the problems.