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Deposit, archive and share your final research data in DR-NTU (Data)

DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

How to deposit?

Useful links: FAQs | Collection Guidelines | NTU Research Data Management | General terms of use and Privacy policy

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72,531 to 72,540 of 72,597 Results
Readme.txt
Sep 19, 2017 - Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation
Plain Text - 384 B - MD5: 2636f89526fdff3d1eed51d5340bbd65
Sig2GRN.jar
Sep 19, 2017 - Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation
application/java-archive - 57.8 KB - MD5: 0616b74779209979bb9399d5c77bc582
Sig2GRN_lib.jar
Sep 19, 2017 - Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation
application/java-archive - 4.8 MB - MD5: 6d2aab7e2e1add1d50e3c636e54ad0a0
src.zip
Sep 19, 2017 - Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation
ZIP Archive - 48.6 KB - MD5: 1b5cbfa3d0ba0ff6c78a5fea99ce3d81
TestingNetwork.txt
Sep 19, 2017 - Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation
Plain Text - 345 B - MD5: 36e78060f6b70687df62c6f28baf3e4a
Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data
Sep 19, 2017 - Knowledge-Guided Fuzzy Logic Network Modeling
Zheng, Jie, 2017, "Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data", https://doi.org/10.21979/N9/VLZWCL, DR-NTU (Data), V1
About Knowledge-guided fuzzy logic network model Knowledge-guided fuzzy logic network model is a new hybrid method to integrate the prior knowledge and data-driven learning for signaling pathway inference. It is applied to infer signaling pathways by exploiting both prior knowled...
cdtw.m
Sep 19, 2017 - Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data
Unknown - 5.5 KB - MD5: 86c556caece399f31eb7a2353a49999b
cell_fate.mat
Sep 19, 2017 - Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data
Unknown - 102.7 KB - MD5: b2d34be66998bc56f13d2f243056d03b
DREAM4.m
Sep 19, 2017 - Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data
Unknown - 1.3 KB - MD5: 99f02624c20d21c009663d7ac8f39e36
DREAM.mat
Sep 19, 2017 - Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data
Unknown - 1.5 KB - MD5: efd4470bb92f49c4a2c84c146576556f
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