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Computational and Structural Biotechnology Journal is a peer-reviewed journal published by Elsevier, covering RNA and protein synthesis mechanisms, Bioinformatics and Genomic Networks, Computational Drug Discovery Methods.
| Publisher | Elsevier |
|---|---|
| Reference style | Numbered (Elsevier) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, C. Lee, A representative article title, Computational and Structural Biotechnology Journal 12 (2023) 45–58.
Formats any DOI in Computational and Structural Biotechnology Journal style. No sign-up. |
| Publishes research in | RNA and protein synthesis mechanisms Bioinformatics and Genomic Networks Computational Drug Discovery Methods Protein Structure and Dynamics Genomics and Phylogenetic Studies |
| ISSN | 2001-0370 |
| Citation impact (2-yr) | 5.77 |
| h-index | 129 |
| i10-index | 2,005 |
| Total citations | 106,340 |
| Article processing charge | $2,642 |
| Open access | Yes |
| Top institutions publishing here | Chinese Academy of Sciences |
| Journal website | www.journals.elsevier.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research…
INTRODUCTION: Extensive research is directed to uncover new biomarkers capable to stratify breast cancer patients into clinically relevant cohorts. However, the overall performance ranking of such marker candidates compared to other genes is virtually absent. Here, we present the ranking of all survival related genes in chemotherapy treated basal and estrogen positive/HER2 negative breast cancer.…
The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in…
UCell is an R package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory than other available methods, enabling the processing of large datasets in a few minutes even on machines with…
Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we introduce the application of digital pathological image analysis using machine learning algorithms, address some problems…
