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- Volume 19, Issue 6, 2024
Current Bioinformatics - Volume 19, Issue 6, 2024
Volume 19, Issue 6, 2024
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Bioinformatic Resources for Plant Genomic Research
Authors: Suvanish Kumar Valsala Sudarsanan and Nidhin SreekumarGenome assembly and annotation are crucial steps in plant genomics research as they provide valuable insights into plant genetic makeup, gene regulation, evolutionary history, and biological processes. In the emergence of high-throughput sequencing technologies, a plethora of genome assembly tools have been developed to meet the diverse needs of plant genome researchers. Choosing the most suitable tool to suit a s Read More
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A Review of Drug-related Associations Prediction Based on Artificial Intelligence Methods
Authors: Mei Ma, Xiujuan Lei and Yuchen ZhangBackground: Predicting drug-related associations is an important task in drug development and discovery. With the rapid advancement of high-throughput technologies and various biological and medical data, artificial intelligence (AI), especially progress in machine learning (ML) and deep learning (DL), has paved a new way for the development of drug-related associations prediction. Many studies have been conducted in t Read More
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A Systematic Review of Medical Expert Systems for Cardiac Arrest Prediction
Authors: Ishleen Kaur, Tanvir Ahmad and M.N. DojaBackground: Predicting cardiac arrest is crucial for timely intervention and improved patient outcomes. Machine learning has yielded astounding results by offering tailored prediction analyses on complex data. Despite advancements in medical expert systems, there remains a need for a comprehensive analysis of their effectiveness and limitations in cardiac arrest prediction. This need arises because there are not enoug Read More
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A Metric to Characterize Differentially Methylated Region Sets Detected from Methylation Array Data
Authors: Xiaoqing Peng, Wanxin Cui, Wenjin Zhang, Zihao Li, Xiaoshu Zhu, Ling Yuan and Ji LiBackground: Identifying differentially methylated region (DMR) is a basic but important task in epigenomics, which can help investigate the mechanisms of diseases and provide methylation biomarkers for screening diseases. A set of methods have been proposed to identify DMRs from methylation array data. However, it lacks effective metrics to characterize different DMR sets and enable a straight way for comparison. Read More
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RDR100: A Robust Computational Method for Identification of Krüppel-like Factors
Authors: Adeel Malik, Majid R. Kamli, Jamal S.M. Sabir, Le Thi Phan, Chang-Bae Kim and Balachandran ManavalanBackground: Krüppel-like factors (KLFs) are a family of transcription factors containing zinc fingers that regulate various cellular processes. KLF proteins are associated with human diseases, such as cancer, cardiovascular diseases, and metabolic disorders. The KLF family consists of 18 members with diverse expression profiles across numerous tissues. Accurate identification and annotation of KLF proteins is crucial, giv Read More
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Volumes & issues
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Volume 20 (2025)
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Volume 19 (2024)
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Volume 18 (2023)
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Volume 17 (2022)
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Volume 16 (2021)
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Volume 15 (2020)
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Volume 14 (2019)
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Volume 13 (2018)
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Volume 12 (2017)
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Volume 11 (2016)
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Volume 10 (2015)
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Volume 9 (2014)
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Volume 8 (2013)
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Volume 7 (2012)
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Volume 6 (2011)
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Volume 5 (2010)
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Volume 4 (2009)
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Volume 3 (2008)
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Volume 2 (2007)
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Volume 1 (2006)
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