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Yifan Pan, Ao Zheng, Guiqi Li and Yuanming Zhang
Although soybean and chickpea belong to the legume family, their seed starch content is very different. Currently, many studies focus on the molecular mechanisms of starch synthesis within a single species. However, the key genes and regulatory relations...
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Sen Ma, Xiaochun Xu, Xiaolong Wang, Yuxin Yang, Yinghua Shi and Yulin Chen
Circular RNAs (circRNAs) are capable of finely modulating gene expression at transcriptional and post-transcriptional levels; however, their characters in dermal papilla cells (DPCs)?the signaling center of hair follicle?are still obscure. Herein, we est...
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Kuan Liu, Haiyuan Liu, Dongyan Sun and Lei Zhang
The reconstruction of gene regulatory networks based on gene expression data can effectively uncover regulatory relationships between genes and provide a deeper understanding of biological control processes. Non-linear dependence is a common problem in t...
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Vidya Manian, Harshini Gangapuram, Jairo Orozco, Heeralal Janwa and Carlos Agrinsoni
Spaceflight microgravity affects normal plant growth in several ways. The transcriptional dataset of the plant model organism Arabidopsis thaliana grown in the international space station is mined using graph-theoretic network analysis approaches to iden...
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Frank Emmert-Streib and Matthias Dehmer
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Angelo Ciaramella and Antonino Staiano
As of today, bioinformatics is one of the most exciting fields of scientific research. There is a wide-ranging list of challenging problems to face, i.e., pairwise and multiple alignments, motif detection/discrimination/classification, phylogenetic tree ...
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Katsuaki Umiji, Koichi Kobayashi and Yuh Yamashita
A probabilistic Boolean network (PBN) is well known as one of the mathematical models of gene regulatory networks. In a Boolean network, expression of a gene is approximated by a binary value, and its time evolution is expressed by Boolean functions. In ...
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Amir Masoud Abdol, Damjan Cicin-Sain, Jaap A. Kaandorp and Anton Crombach
Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational ...
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