Shanghai Maritime

Oct 23, 2024 | bmcbioinformatics.biomedcentral.com | Shanghai Maritime

In this study, five-fold cross-validation [40] was adopted to evaluate the performance of the models. When conducting the cross-validation, we denoted 9589 validated CMAs as positive samples. Meanwhile, the negative samples were randomly selected from unlabeled associations, and their number was the same as that of the positive samples. All samples were randomly and equally divided into five sets. Each set was selected as a test set one by one, and the remaining sets constituted the training set.

Sep 30, 2024 | journals.plos.org | Shanghai Maritime |Jiawei Ge |Shanghai Jiaotong

Citation: Li Y, Yin M, Ge J (2024) The impact of port green competitiveness on the hinterland economy: A case study of China. PLoS ONE 19(9): e0311221. https://doi.org/10.1371/journal.pone.0311221Editor: Cigdem Kadaifci, Istanbul Technical University: Istanbul Teknik Universitesi, TÜRKIYEReceived: May 26, 2024; Accepted: September 16, 2024; Published: September 30, 2024Copyright: © 2024 Li et al.

Aug 23, 2024 | journals.plos.org | Zhuan Li |Shanghai Maritime |Jin Liu |Hengyang Wang

Citation: Li Z, Liu J, Wang H, Zhang X, Wu Z, Han B (2024) VT-3DCapsNet: Visual tempos 3D-Capsule network for video-based facial expression recognition. PLoS ONE 19(8): e0307446. https://doi.org/10.1371/journal.pone.0307446Editor: Qionghao Huang, Zhejiang Normal University, CHINAReceived: May 12, 2023; Accepted: July 5, 2024; Published: August 23, 2024Copyright: © 2024 Li et al.

Aug 17, 2024 | academic.oup.com | Shanghai Maritime

MicroRNAs (miRNAs) are a class of short non-coding RNA molecules [1, 2], typically composed of ~20 nucleotides. They have been extensively studied due to their pivotal roles in cellular regulation [3–6]. The miRNAs are involved in the regulation of various biological processes, such as cell proliferation, differentiation and apoptosis, by binding to the mRNA of target genes [1, 7–9].

Jan 29, 2024 | bmcbioinformatics.biomedcentral.com | Shanghai Maritime

In this study, a new multi-label classifier, PredictEFC, was designed to identify family classes of enzymes, which adopted the compact features derived from proteins’ functional domain information via a novel feature extraction scheme. The entire construction and evaluation procedures are illustrated in Fig. 2. Entire construction and evaluation procedures of PredictEFC. The enzymes and their EC numbers are retrieved from Expasy.