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Article
Peer-Review Record

Identification of Cardiovascular Disease-Related Genes Based on the Co-Expression Network Analysis of Genome-Wide Blood Transcriptome

Cells 2022, 11(18), 2867; https://doi.org/10.3390/cells11182867
by Taesic Lee 1,2,†, Sangwon Hwang 3,†, Dong Min Seo 4, Ha Chul Shin 5, Hyun Soo Kim 5, Jang-Young Kim 6 and Young Uh 7,*
Reviewer 1:
Reviewer 2: Anonymous
Cells 2022, 11(18), 2867; https://doi.org/10.3390/cells11182867
Submission received: 19 July 2022 / Revised: 26 August 2022 / Accepted: 10 September 2022 / Published: 14 September 2022

Round 1

Reviewer 1 Report

Please refer to the attached file. 

Comments for author File: Comments.pdf

Author Response

The independent PDF file including answers to reviewer's comments was uploaded. 

Author Response File: Author Response.pdf

Reviewer 2 Report

In this manuscript, Lee et al describe their approach to identifying genes related to cardiovascular diseases (CVDs) using the co-expression network analysis of genome-wide 3 blood transcriptome. This is an interesting topic as CVDs in one of the major causes of death globally. Identifying CVD-related genes may contribute to the prevention and/or treatment of the disease. The manuscript is well written and the results/main findings are extensively discussed. However, I have some minor suggestions that can be incorporated to strengthen the review as follows:

1.       The introduction should be more informative and the aim of this work should be clearly stated in the last paragraph (LL 63-72)

2.       LL 244-245. Please provide the name of the three databases

3.       The authors should provide some suggestions for future studies.

Author Response

The independent PDF file including answers to reviewer's comments was uploaded.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The authors have addressed my previous comments. 

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