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Machine Learning and Artificial Intelligence in Bioinformatics

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  1. The Cox proportional hazards model is commonly used to predict hazard ratio, which is the risk or probability of occurrence of an event of interest. However, the Cox proportional hazard model cannot directly g...

    Authors: Eu-Tteum Baek, Hyung Jeong Yang, Soo Hyung Kim, Guee Sang Lee, In-Jae Oh, Sae-Ryung Kang and Jung-Joon Min

    Citation: BMC Bioinformatics 2021 22:192

    Content type: Methodology article

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  2. The genomics data analysis has been widely used to study disease genes and drug targets. However, the existence of missing values in genomics datasets poses a significant problem, which severely hinders the us...

    Authors: Xinshan Zhu, Jiayu Wang, Biao Sun, Chao Ren, Ting Yang and Jie Ding

    Citation: BMC Bioinformatics 2021 22:188

    Content type: Methodology article

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  3. Technological and research advances have produced large volumes of biomedical data. When represented as a network (graph), these data become useful for modeling entities and interactions in biological and simi...

    Authors: Khushnood Abbas, Alireza Abbasi, Shi Dong, Ling Niu, Laihang Yu, Bolun Chen, Shi-Min Cai and Qambar Hasan

    Citation: BMC Bioinformatics 2021 22:187

    Content type: Research article

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  4. Microsatellite instability (MSI) is a common genomic alteration in colorectal cancer, endometrial carcinoma, and other solid tumors. MSI is characterized by a high degree of polymorphism in microsatellite leng...

    Authors: Tao Zhou, Libin Chen, Jing Guo, Mengmeng Zhang, Yanrui Zhang, Shanbo Cao, Feng Lou and Haijun Wang

    Citation: BMC Bioinformatics 2021 22:185

    Content type: Software

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  5. The interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabolism, which is of extraordinary significance to modern proteomics resea...

    Authors: Yang Wang, Zhanchao Li, Yanfei Zhang, Yingjun Ma, Qixing Huang, Xingyu Chen, Zong Dai and Xiaoyong Zou

    Citation: BMC Bioinformatics 2021 22:184

    Content type: Research article

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  6. Identifying lncRNA-disease associations not only helps to better comprehend the underlying mechanisms of various human diseases at the lncRNA level but also speeds up the identification of potential biomarkers...

    Authors: Rong Zhu, Yong Wang, Jin-Xing Liu and Ling-Yun Dai

    Citation: BMC Bioinformatics 2021 22:175

    Content type: Methodology article

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  7. Supervised learning from high-throughput sequencing data presents many challenges. For one, the curse of dimensionality often leads to overfitting as well as issues with scalability. This can bring about inacc...

    Authors: Trevor S. Frisby, Shawn J. Baker, Guillaume Marçais, Quang Minh Hoang, Carl Kingsford and Christopher J. Langmead

    Citation: BMC Bioinformatics 2021 22:174

    Content type: Methodology article

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  8. To address the need for easy and reliable species classification in plant genetic resources collections, we assessed the potential of five classifiers (Random Forest, Neighbour-Joining, 1-Nearest Neighbour, a ...

    Authors: Artur van Bemmelen van der Plaat, Rob van Treuren and Theo J. L. van Hintum

    Citation: BMC Bioinformatics 2021 22:173

    Content type: Research article

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  9. Recent studies have confirmed that N7-methylguanosine (m7G) modification plays an important role in regulating various biological processes and has associations with multiple diseases. Wet-lab experiments are cos...

    Authors: Jiani Ma, Lin Zhang, Jin Chen, Bowen Song, Chenxuan Zang and Hui Liu

    Citation: BMC Bioinformatics 2021 22:152

    Content type: Software

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  10. Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive. ...

    Authors: Kevin De Angeli, Shang Gao, Mohammed Alawad, Hong-Jun Yoon, Noah Schaefferkoetter, Xiao-Cheng Wu, Eric B. Durbin, Jennifer Doherty, Antoinette Stroup, Linda Coyle, Lynne Penberthy and Georgia Tourassi

    Citation: BMC Bioinformatics 2021 22:113

    Content type: Research article

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  11. Manual microscopic examination of Leishman/Giemsa stained thin and thick blood smear is still the “gold standard” for malaria diagnosis. One of the drawbacks of this method is that its accuracy, consistency, a...

    Authors: Fetulhak Abdurahman, Kinde Anlay Fante and Mohammed Aliy

    Citation: BMC Bioinformatics 2021 22:112

    Content type: Research article

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  12. Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more imp...

    Authors: Mateusz Garbulowski, Klev Diamanti, Karolina Smolińska, Nicholas Baltzer, Patricia Stoll, Susanne Bornelöv, Aleksander Øhrn, Lars Feuk and Jan Komorowski

    Citation: BMC Bioinformatics 2021 22:110

    Content type: Software

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  13. The accumulation of various multi-omics data and computational approaches for data integration can accelerate the development of precision medicine. However, the algorithm development for multi-omics data inte...

    Authors: Yuqi Wen, Xinyu Song, Bowei Yan, Xiaoxi Yang, Lianlian Wu, Dongjin Leng, Song He and Xiaochen Bo

    Citation: BMC Bioinformatics 2021 22:97

    Content type: Methodology article

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  14. Microbes perform a fundamental economic, social, and environmental role in our society. Metagenomics makes it possible to investigate microbes in their natural environments (the complex communities) and their ...

    Authors: Raíssa Silva, Kleber Padovani, Fabiana Góes and Ronnie Alves

    Citation: BMC Bioinformatics 2021 22:87

    Content type: Software

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  15. The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting thes...

    Authors: Camilo Broc, Therese Truong and Benoit Liquet

    Citation: BMC Bioinformatics 2021 22:86

    Content type: Methodology article

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  16. In the last decade, Genome-wide Association studies (GWASs) have contributed to decoding the human genome by uncovering many genetic variations associated with various diseases. Many follow-up investigations i...

    Authors: Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar, Wei Wu and Eric P. Xing

    Citation: BMC Bioinformatics 2021 22:50

    Content type: Methodology article

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  17. Survival analysis is an important part of cancer studies. In addition to the existing Cox proportional hazards model, deep learning models have recently been proposed in survival prediction, which directly int...

    Authors: Jiarui Feng, Heming Zhang and Fuhai Li

    Citation: BMC Bioinformatics 2021 22:47

    Content type: Methodology article

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  18. Differential expression and feature selection analyses are essential steps for the development of accurate diagnostic/prognostic classifiers of complicated human diseases using transcriptomics data. These step...

    Authors: Liangqun Lu, Kevin A. Townsend and Bernie J. Daigle Jr.

    Citation: BMC Bioinformatics 2021 22:44

    Content type: Methodology article

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  19. Assigning chromatin states genome-wide (e.g. promoters, enhancers, etc.) is commonly performed to improve functional interpretation of these states. However, computational methods to assign chromatin state suf...

    Authors: Tara Eicher, Jany Chan, Han Luu, Raghu Machiraju and Ewy A. Mathé

    Citation: BMC Bioinformatics 2021 22:35

    Content type: Methodology article

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  20. Predicting the response of cancer cell lines to specific drugs is an essential problem in personalized medicine. Since drug response is closely associated with genomic information in cancer cells, some large p...

    Authors: Akram Emdadi and Changiz Eslahchi

    Citation: BMC Bioinformatics 2021 22:33

    Content type: Methodology article

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  21. Drug repositioning is an emerging approach in pharmaceutical research for identifying novel therapeutic potentials for approved drugs and discover therapies for untreated diseases. Due to its time and cost eff...

    Authors: Tamer N. Jarada, Jon G. Rokne and Reda Alhajj

    Citation: BMC Bioinformatics 2021 22:28

    Content type: Research article

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  22. Currently, large-scale gene expression profiling has been successfully applied to the discovery of functional connections among diseases, genetic perturbation, and drug action. To address the cost of an ever-e...

    Authors: Lingpeng Kong, Yuanyuan Chen, Fengjiao Xu, Mingmin Xu, Zutan Li, Jingya Fang, Liangyun Zhang and Cong Pian

    Citation: BMC Bioinformatics 2021 22:27

    Content type: Methodology article

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  23. Diverse microbiome communities drive biogeochemical processes and evolution of animals in their ecosystems. Many microbiome projects have demonstrated the power of using metagenomics to understand the structur...

    Authors: Eliza Dhungel, Yassin Mreyoud, Ho-Jin Gwak, Ahmad Rajeh, Mina Rho and Tae-Hyuk Ahn

    Citation: BMC Bioinformatics 2021 22:25

    Content type: Software

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  24. Querying drug-induced gene expression profiles with machine learning method is an effective way for revealing drug mechanism of actions (MOAs), which is strongly supported by the growth of large scale and high...

    Authors: Shengqiao Gao, Lu Han, Dan Luo, Gang Liu, Zhiyong Xiao, Guangcun Shan, Yongxiang Zhang and Wenxia Zhou

    Citation: BMC Bioinformatics 2021 22:17

    Content type: Research article

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  25. One of the current directions of precision medicine is the use of computational methods to aid in the diagnosis, prognosis, and treatment of disease based on data driven approaches. For instance, in oncology, ...

    Authors: Joshua D. Mannheimer, Ashok Prasad and Daniel L. Gustafson

    Citation: BMC Bioinformatics 2021 22:15

    Content type: Research article

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  26. Accurate prediction of binding between class I human leukocyte antigen (HLA) and neoepitope is critical for target identification within personalized T-cell based immunotherapy. Many recent prediction tools de...

    Authors: Yilin Ye, Jian Wang, Yunwan Xu, Yi Wang, Youdong Pan, Qi Song, Xing Liu and Ji Wan

    Citation: BMC Bioinformatics 2021 22:7

    Content type: Research article

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  27. Protein phosphoglycerylation, the addition of a 1,3-bisphosphoglyceric acid (1,3-BPG) to a lysine residue of a protein and thus to form a 3-phosphoglyceryl-lysine, is a reversible and non-enzymatic post-transl...

    Authors: Kai-Yao Huang, Fang-Yu Hung, Hui-Ju Kao, Hui-Hsuan Lau and Shun-Long Weng

    Citation: BMC Bioinformatics 2020 21:568

    Content type: Research article

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  28. The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolut...

    Authors: Giulio Caravagna, Guido Sanguinetti, Trevor A. Graham and Andrea Sottoriva

    Citation: BMC Bioinformatics 2020 21:531

    Content type: Software

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  29. Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine ...

    Authors: Liang-Chin Huang, Wayland Yeung, Ye Wang, Huimin Cheng, Aarya Venkat, Sheng Li, Ping Ma, Khaled Rasheed and Natarajan Kannan

    Citation: BMC Bioinformatics 2020 21:520

    Content type: Research article

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  30. The formation of contacts among protein secondary structure elements (SSEs) is an important step in protein folding as it determines topology of protein tertiary structure; hence, inferring inter-SSE contacts ...

    Authors: Qi Zhang, Jianwei Zhu, Fusong Ju, Lupeng Kong, Shiwei Sun, Wei-Mou Zheng and Dongbo Bu

    Citation: BMC Bioinformatics 2020 21:503

    Content type: Methodology

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  31. The use of predictive gene signatures to assist clinical decision is becoming more and more important. Deep learning has a huge potential in the prediction of phenotype from gene expression profiles. However, ...

    Authors: Blaise Hanczar, Farida Zehraoui, Tina Issa and Mathieu Arles

    Citation: BMC Bioinformatics 2020 21:501

    Content type: Research article

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  32. Many studies prove that miRNAs have significant roles in diagnosing and treating complex human diseases. However, conventional biological experiments are too costly and time-consuming to identify unconfirmed m...

    Authors: Lei Zhang, Bailong Liu, Zhengwei Li, Xiaoyan Zhu, Zhizhen Liang and Jiyong An

    Citation: BMC Bioinformatics 2020 21:470

    Content type: Methodology article

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  33. MicroRNAs (miRNAs) are non-coding RNAs with regulatory functions. Many studies have shown that miRNAs are closely associated with human diseases. Among the methods to explore the relationship between the miRNA...

    Authors: Tian-Ru Wu, Meng-Meng Yin, Cui-Na Jiao, Ying-Lian Gao, Xiang-Zhen Kong and Jin-Xing Liu

    Citation: BMC Bioinformatics 2020 21:454

    Content type: Methodology article

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  34. Recent studies have shown that N6-methyladenosine (m6A) plays a critical role in numbers of biological processes and complex human diseases. However, the regulatory mechanisms of most methylation sites remain unc...

    Authors: Lin Zhang, Shutao Chen, Jingyi Zhu, Jia Meng and Hui Liu

    Citation: BMC Bioinformatics 2020 21:447

    Content type: Research article

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  35. As a machine learning method with high performance and excellent generalization ability, extreme learning machine (ELM) is gaining popularity in various studies. Various ELM-based methods for different fields ...

    Authors: Liang-Rui Ren, Ying-Lian Gao, Jin-Xing Liu, Junliang Shang and Chun-Hou Zheng

    Citation: BMC Bioinformatics 2020 21:445

    Content type: Methodology article

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  36. A typical task in bioinformatics consists of identifying which features are associated with a target outcome of interest and building a predictive model. Automated machine learning (AutoML) systems such as the...

    Authors: Elisabetta Manduchi, Weixuan Fu, Joseph D. Romano, Stefano Ruberto and Jason H. Moore

    Citation: BMC Bioinformatics 2020 21:430

    Content type: Methodology article

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  37. The treatment of complex diseases by taking multiple drugs becomes increasingly popular. However, drug-drug interactions (DDIs) may give rise to the risk of unanticipated adverse effects and even unknown toxic...

    Authors: Yue-Hua Feng, Shao-Wu Zhang and Jian-Yu Shi

    Citation: BMC Bioinformatics 2020 21:419

    Content type: Methodology article

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