💸The benefits and threats of blockchain technology in healthcare: A scoping review
📘Journal: International Journal of Medical Informatics (I.F.=4.046)
🗓Publish year: 2020
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📲Channel: @Bioinformatics
📘Journal: International Journal of Medical Informatics (I.F.=4.046)
🗓Publish year: 2020
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📲Channel: @Bioinformatics
👍4
📜Artificial intelligence in cancer research: learning at different levels of data granularity
📘Journal: Molecular Oncology Journal (I.F.=6.603)
🗓Publish year: 2021
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📲Channel: @Bioinformatics
📘Journal: Molecular Oncology Journal (I.F.=6.603)
🗓Publish year: 2021
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📲Channel: @Bioinformatics
👍2
📑Advances in clinical genetics and genomics
💥Review paper
📘Journal: Intelligent Medicine
🗓Publish year: September 2021
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📲Channel: @Bioinformatics
💥Review paper
📘Journal: Intelligent Medicine
🗓Publish year: September 2021
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📲Channel: @Bioinformatics
👍1
📃Protein domain identification methods and online resources
📘Journal: Computational and Structural Biotechnology (I.F.=7.271)
🗓Publish year: 2021
💥Abstract: Protein domains are the basic units of proteins that can fold, function, and evolve independently. Knowledge of protein domains is critical for protein classification, understanding their biological functions, annotating their evolutionary mechanisms and protein design. Thus, many protein domain identification approaches have been developed, and a variety of protein domain databases have also been constructed. This review divides protein domain prediction methods into two categories, sequence-based and structure-based. These methods are introduced in detail, and their advantages and limitations are compared. Furthermore, this review also provides a comprehensive overview of popular online protein domain sequence and structure databases. Finally, we discuss potential improvements of these prediction methods.
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📲Channel: @Bioinformatics
📘Journal: Computational and Structural Biotechnology (I.F.=7.271)
🗓Publish year: 2021
💥Abstract: Protein domains are the basic units of proteins that can fold, function, and evolve independently. Knowledge of protein domains is critical for protein classification, understanding their biological functions, annotating their evolutionary mechanisms and protein design. Thus, many protein domain identification approaches have been developed, and a variety of protein domain databases have also been constructed. This review divides protein domain prediction methods into two categories, sequence-based and structure-based. These methods are introduced in detail, and their advantages and limitations are compared. Furthermore, this review also provides a comprehensive overview of popular online protein domain sequence and structure databases. Finally, we discuss potential improvements of these prediction methods.
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📲Channel: @Bioinformatics
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🎞 Biology meets programming: Bioinformatics 101 for NGS researchers
💥Free recorded webinar from Science
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📲Channel: @Bioinformatics
💥Free recorded webinar from Science
🌐 Watch
📲Channel: @Bioinformatics
www.science.org
Biology meets programming: Bioinformatics 101 for NGS researchers
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📑A review of protein–protein interaction network alignment: From pathway comparison to global alignment
📘Journal: Computational and Structural Biotechnology (I.F.=7.271)
🗓Publish year: 202o
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📲Channel: @Bioinformatics
📘Journal: Computational and Structural Biotechnology (I.F.=7.271)
🗓Publish year: 202o
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📲Channel: @Bioinformatics
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📽Life After Graduation: Bioinformatics edition
💥Free webinar
🎫 Free E-Certificate
🗓 Date: Saturday, 22 Jan 2022
🕐 Time: 14:00 – 16:00 PM WIB
📍Location: ZOOM
✍️ Registration
ℹ️ More information
📲Channel: @Bioinformatics
💥Free webinar
🎫 Free E-Certificate
🗓 Date: Saturday, 22 Jan 2022
🕐 Time: 14:00 – 16:00 PM WIB
📍Location: ZOOM
✍️ Registration
ℹ️ More information
📲Channel: @Bioinformatics
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👨🏻💻Free Online hands-on Workshop
💥Best Practices for Scientific Computing
🗓 Date: Jan 24 - 27, 2022
⌚️ Time: 12:00 pm - 4:00 pm EST
▫️You don't need to have any previous knowledge of the tools that will be presented at the workshop
ℹ️ More information
📲Channel: @Bioinformatics
💥Best Practices for Scientific Computing
🗓 Date: Jan 24 - 27, 2022
⌚️ Time: 12:00 pm - 4:00 pm EST
▫️You don't need to have any previous knowledge of the tools that will be presented at the workshop
ℹ️ More information
📲Channel: @Bioinformatics
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👷Remote Job: Bioinformatics Analyst
💥Job summery: Primary accountability is to leverage the organization’s data assets exome sequencing data (>180,000 individuals) from MyCode Community Health Initiative to improve quality, efficiency and generate knowledge specifically in the field of bioinformatics within health research. Performs and supervises complex data extraction, transformation, visualization, and summarization to support Research and operations activities.. Uses data reporting/management tools such as SQL, python, NGS tools (GATK, BWA, VEP, etc.), genomic databases (ClinVar, NCBI, gnomAD, etc.) and contributes to national publications. Uses multiple operating systems (Windows, Linux) and compute environments (local, cloud) and is responsible for assisting in development and maintenance of bioinformatics capabilities.
ℹ️ More information and apply
📲Channel: @Bioinformatics
💥Job summery: Primary accountability is to leverage the organization’s data assets exome sequencing data (>180,000 individuals) from MyCode Community Health Initiative to improve quality, efficiency and generate knowledge specifically in the field of bioinformatics within health research. Performs and supervises complex data extraction, transformation, visualization, and summarization to support Research and operations activities.. Uses data reporting/management tools such as SQL, python, NGS tools (GATK, BWA, VEP, etc.), genomic databases (ClinVar, NCBI, gnomAD, etc.) and contributes to national publications. Uses multiple operating systems (Windows, Linux) and compute environments (local, cloud) and is responsible for assisting in development and maintenance of bioinformatics capabilities.
ℹ️ More information and apply
📲Channel: @Bioinformatics
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📑Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale
📘Journal: Frontiers in Bioinformatics
🗓Publish year: 2022
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📲Channel: @Bioinformatics
👍3
📑 Artificial Intelligence and Machine Learning in Precision and Genomic Medicine
📘 Preprint paper
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📲Channel: @Bioinformatics
📘 Preprint paper
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📲Channel: @Bioinformatics
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📃Statistics or biology: the zero-inflation controversy about scRNA-seq data
📘Journal: Genome Biology (I.F.=13.583)
🗓Publish year: 2022
💥Abstract: Researchers view vast zeros in single-cell RNA-seq data differently: some regard zeros as biological signals representing no or low gene expression, while others regard zeros as missing data to be corrected. To help address the controversy, here we discuss the sources of biological and non-biological zeros; introduce five mechanisms of adding non-biological zeros in computational benchmarking; evaluate the impacts of non-biological zeros on data analysis; benchmark three input data types: observed counts, imputed counts, and binarized counts; discuss the open questions regarding non-biological zeros; and advocate the importance of transparent analysis.
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📲Channel: @Bioinformatics
📘Journal: Genome Biology (I.F.=13.583)
🗓Publish year: 2022
💥Abstract: Researchers view vast zeros in single-cell RNA-seq data differently: some regard zeros as biological signals representing no or low gene expression, while others regard zeros as missing data to be corrected. To help address the controversy, here we discuss the sources of biological and non-biological zeros; introduce five mechanisms of adding non-biological zeros in computational benchmarking; evaluate the impacts of non-biological zeros on data analysis; benchmark three input data types: observed counts, imputed counts, and binarized counts; discuss the open questions regarding non-biological zeros; and advocate the importance of transparent analysis.
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📲Channel: @Bioinformatics
👍4❤1
📃Design, delivery and evaluation of a bioinformatics education workshop for 13-16-year-olds
📘Journal: Genome Biology (I.F.=1.262)
🗓Publish year: 2021
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📲Channel: @Bioinformatics
📘Journal: Genome Biology (I.F.=1.262)
🗓Publish year: 2021
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📲Channel: @Bioinformatics
Taylor & Francis
Design, delivery and evaluation of a bioinformatics education workshop for 13-16-year-olds
Bioinformatics is the use of computers in biology, particularly to analyse DNA and protein sequences and associated data. Bioinformatics has become crucial to most areas of life sciences research. ...
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📑Machine learning for multi-omics data integration in cancer
📘Journal: IScience (I.F.=5.458)
🗓Publish year: 2022
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📲Channel: @Bioinformatics
📘Journal: IScience (I.F.=5.458)
🗓Publish year: 2022
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📲Channel: @Bioinformatics
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📺 BioInformatics: Algorithms and Applications
💥YouTube playlists curated by Class Central (69 sessions)
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📲Channel: @Bioinformatics
💥YouTube playlists curated by Class Central (69 sessions)
🌐 Watch
📲Channel: @Bioinformatics
📑A Bibliometric Analysis of Mexican Bioinformatics: A Portrait of Actors, Structure, and Dynamics
📘Journal: Biology (I.F.=5.079)
🗓Publish year: 2022
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📲Channel: @Bioinformatics
📘Journal: Biology (I.F.=5.079)
🗓Publish year: 2022
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📲Channel: @Bioinformatics
👍3❤1
📄Recent Advances of Deep Learning in Bioinformatics and Computational Biology
📘Journal: Frontiers in Genetics (I.F.=5.599)
🗓Publish year: 2019
💥Abstract: Extracting inherent valuable knowledge from omics big data remains as a daunting problem in bioinformatics and computational biology. Deep learning, as an emerging branch from machine learning, has exhibited unprecedented performance in quite a few applications from academia and industry. We highlight the difference and similarity in widely utilized models in deep learning studies, through discussing their basic structures, and reviewing diverse applications and disadvantages. We anticipate the work can serve as a meaningful perspective for further development of its theory, algorithm and application in bioinformatic and computational biology.
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📲Channel: @Bioinformatics
📘Journal: Frontiers in Genetics (I.F.=5.599)
🗓Publish year: 2019
💥Abstract: Extracting inherent valuable knowledge from omics big data remains as a daunting problem in bioinformatics and computational biology. Deep learning, as an emerging branch from machine learning, has exhibited unprecedented performance in quite a few applications from academia and industry. We highlight the difference and similarity in widely utilized models in deep learning studies, through discussing their basic structures, and reviewing diverse applications and disadvantages. We anticipate the work can serve as a meaningful perspective for further development of its theory, algorithm and application in bioinformatic and computational biology.
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📲Channel: @Bioinformatics
👍6❤1
🎬 Free webinar
💥Deciphering the cellular, molecular, clinical and therapeutic implications of lung cancers lacking targeted therapies
🗓 Date: 15th February
🕖 Time: From 19 to 20 p.m, CET
🇬🇧Language: English
ℹ️ Registration and more information
📲Channel: @Bioinformatics
💥Deciphering the cellular, molecular, clinical and therapeutic implications of lung cancers lacking targeted therapies
🗓 Date: 15th February
🕖 Time: From 19 to 20 p.m, CET
🇬🇧Language: English
ℹ️ Registration and more information
📲Channel: @Bioinformatics
Eventbrite
BioInfoClub | Bioinformatic study of lung cancers without therapies
Deciphering the cellular, molecular, clinical and therapeutic implications of lung cancers lacking targeted therapies
👨🏫 Free Online Course:
Artificial Intelligence in Bioinformatics
🗓 Duration: 3 weeks (Self paced)
💥What you'll learn:
▫️Overview on bioinformatics
▫️Artificial Intelligence and how to apply it to bioinformatics
▫️Feature engineering
▫️Feature learning
▫️Deep learning in bioinformatics
▫️Analyzing and visualizing data
ℹ️ More information and Participation
📲Channel: @Bioinformatics
Artificial Intelligence in Bioinformatics
🗓 Duration: 3 weeks (Self paced)
💥What you'll learn:
▫️Overview on bioinformatics
▫️Artificial Intelligence and how to apply it to bioinformatics
▫️Feature engineering
▫️Feature learning
▫️Deep learning in bioinformatics
▫️Analyzing and visualizing data
ℹ️ More information and Participation
📲Channel: @Bioinformatics
FutureLearn
Artificial Intelligence in Bioinformatics - Online AI Course - FutureLearn
Join Taipei University’s online course to explore how AI is transforming the field of bioinformatics, and build your working knowledge of AI-based bioinformatics.
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