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ACM SIGBioinformatics Record is a peer-reviewed journal published by ACM, covering Genetics, Bioinformatics, and Biomedical Research, Bioinformatics and Genomic Networks, Gene expression and cancer classification.
| Publisher | ACM |
|---|---|
| Reference style | Numbered (ACM) Numbered — [1], [2] in the text [1] Ada Smith, Ben Jones, and Cara Lee. 2023. A representative article title. ACM SIGBioinformatics Record 12, 3, Article 45 (2023).
Formats any DOI in ACM SIGBioinformatics Record style. No sign-up. |
| Publishes research in | Genetics, Bioinformatics, and Biomedical Research Bioinformatics and Genomic Networks Gene expression and cancer classification Gene Regulatory Network Analysis Artificial Intelligence in Healthcare |
| ISSN | 2159-1210 |
| h-index | 5 |
| i10-index | 1 |
| Total citations | 74 |
| Top institutions publishing here | Magna Graecia University |
| 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.
A plethora of biologically useful information lies obscured in the genomes of organisms. Encoded within the genome of an organism is the information about its evolutionary history. Evolutionary signals are scattered throughout the genome. Bioinformatics approaches are frequently invoked to deconstruct the evolutionary patterns underlying genomes, which are difficult to decipher using traditional laboratory experiments.…
The key mission of Healthcare industry is improving lives through better healthcare solutions. Technical innovations in the last decade have led to solutions that are safe, cost effective, high-quality and easily accessible. A wide variety of computational techniques, storage techniques, softwares and tools are already shaping the future of healthcare. In this paper we have…
The cancer research community requires a standardized way of describing mathematical and computational models to enable interoperation between systems, repositories, and between the models themselves. In this paper we describe a new markup language, TumorML, for describing computational models that fall within the domain of cancer. TumorML is an XML-based markup language that wraps existing…
The analysis of biomedical signals and images is relevant for early diagnosis, detection and treatment of diseases. It represents the first step in the proper management of pathological conditions. Therefore, it is essential to support clinical practice during the diagnosis process by extracting relevant information and by classifying different diseases. This contribution outlines the methodologies…
A high level of expertise, rigorous algorithms and methods are needed to adequately mine and harness Mass Spectrometer generated data due to its unique nature and structure. Hitherto, peptide ions are matched with theoretical results and/or public databases in order to identify expressed proteins in analyzed protein source samples, but this is done on a…
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