📃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
🖇 Study the paper
📲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)
🌐 Watch
📲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
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📄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.
🌐 Study the paper
📲Channel: @Bioinformatics
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🎬 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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📑Ten Simple Rules for writing algorithmic bioinformatics conference papers
📘Journal: PLOS Computational Biology (I.F.=4.475)
🗓Publish year: 2020
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📲Channel: @Bioinformatics
📘Journal: PLOS Computational Biology (I.F.=4.475)
🗓Publish year: 2020
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📲Channel: @Bioinformatics
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🎖 11th ISCB Student Wikipedia competition announcement
The competition aims to improve Wikipedia's coverage of any topic relating to ISCB's Bioinformatics Core Competencies
💣 Deadline: 29 April 2022
🏆Prizes:
🥇1st prize - $500 (USD) and 1 year membership to the ISCB
🥈2nd prize - $250 (USD) and 1 year membership to the ISCB
🥉3rd prize - $150 (USD) and 1 year membership to the ISCB
ℹ️ More information
📲Channel: @Bioinformatics
The competition aims to improve Wikipedia's coverage of any topic relating to ISCB's Bioinformatics Core Competencies
💣 Deadline: 29 April 2022
🏆Prizes:
🥇1st prize - $500 (USD) and 1 year membership to the ISCB
🥈2nd prize - $250 (USD) and 1 year membership to the ISCB
🥉3rd prize - $150 (USD) and 1 year membership to the ISCB
ℹ️ More information
📲Channel: @Bioinformatics
Wikipedia
Wikipedia:WikiProject Molecular Biology/Computational Biology/11th ISCB Student Wikipedia competition announcement
The International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology announce the 11th ISCB Student Wikipedia Competition: the competition aims to improve Wikipedia's coverage of any topic relating…
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🎬 Free webinar
🇪🇸Big data and Artificial Intelligence: towards personalized medicine
🗓 Date: 4 February, 2022
🕖 Time: 12:30 p.m.
ℹ️ Participate (in Microsoft Teams)
📲Channel: @Bioinformatics
🇪🇸Big data and Artificial Intelligence: towards personalized medicine
🗓 Date: 4 February, 2022
🕖 Time: 12:30 p.m.
ℹ️ Participate (in Microsoft Teams)
📲Channel: @Bioinformatics
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🎬 Free webinar hosted by the Genomic Institute
💥Genomics in Practice
🗓 Date: Thursday 24 February
🕖 Time: 4:00pm to 5:30pm AEST
ℹ️ More information
✍🏻 Registration
📲Channel: @Bioinformatics
💥Genomics in Practice
🗓 Date: Thursday 24 February
🕖 Time: 4:00pm to 5:30pm AEST
ℹ️ More information
✍🏻 Registration
📲Channel: @Bioinformatics
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🎬 Free webinar
💥Biomarker Discovery from Gene Expression: Challenges and Solutions for Success
🗓 Date: Thursday 24 February
🕖 Time: 11am EST (NA) / 4pm GMT (UK) / 5pm CET (EU-Central)
ℹ️ More information
✍🏻 Registration (Creating an account is required)
📲Channel: @Bioinformatics
💥Biomarker Discovery from Gene Expression: Challenges and Solutions for Success
🗓 Date: Thursday 24 February
🕖 Time: 11am EST (NA) / 4pm GMT (UK) / 5pm CET (EU-Central)
ℹ️ More information
✍🏻 Registration (Creating an account is required)
📲Channel: @Bioinformatics
Xtalks
Biomarker Discovery from Gene Expression: Challenges and Solutions for Success
Join this webinar to learn about biomarker discovery from gene expression and bioinformatics innovations with case study examples.
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🎞Introduction to Glycoinformatics
💥Free online recent course
▫️Part 1
▫️Part 2
▫️Part 3
▫️Part 4
📲Channel: @Bioinformatics
💥Free online recent course
▫️Part 1
▫️Part 2
▫️Part 3
▫️Part 4
📲Channel: @Bioinformatics
YouTube
Introduction to Glycoinformatics (1 of 4)
Glycan molecules decorate a broad variety of surface or secreted proteins and the literature is filled with unnoticed references focusing on the “glyco” part of glycoproteins. This course is an opportunity to update and extend your knowledge of glycoproteins…
👨🏫 Registration is open for One month Bioinformatics Workshop
💥 Data science and Machine learning for Bioinformatics with "R"💥
🗓 Duration: 19 February - 18 March, 2022
✍️ Registration Link
https://decodelife.co.in
💲 Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
💥Key Features:
▫️ 20 sessions with approximately 35 hrs of learning
▫️E- Certificate of Participation
📲Channel: @Bioinformatics
💥 Data science and Machine learning for Bioinformatics with "R"💥
🗓 Duration: 19 February - 18 March, 2022
✍️ Registration Link
https://decodelife.co.in
💲 Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
💥Key Features:
▫️ 20 sessions with approximately 35 hrs of learning
▫️E- Certificate of Participation
📲Channel: @Bioinformatics
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⏺Free recorded webinar
🎥What single-cell RNA-sequencing is, and the workflow in terms of quality control, clustering and differential gene expression analysis
🌐 Watch
📲Channel: @Bioinformatics
🎥What single-cell RNA-sequencing is, and the workflow in terms of quality control, clustering and differential gene expression analysis
🌐 Watch
📲Channel: @Bioinformatics
YouTube
Analysis workflow for single-cell RNA-sequencing data
In this presentation, Fios Genomics Bioinformatician Katerina Boufea talks through an analysis workflow for single-cell RNA-sequencing data. She explains what single-cell RNA-sequencing is before going on to discuss the workflow in terms of quality control…
👩⚕️Computational healthcare: Present and future perspectives (Review)
📘Journal: Experimental and Therapeutic Medicine (I.F.=2.447)
🗓Publish year: September 2021
💥 Abstract: Artificial intelligence (AI) has been developed through repeated new discoveries since around 1960. The use of AI is now becoming widespread within society and our daily lives. AI is also being introduced into healthcare, such as medicine and drug development; however, it is currently biased towards specific domains. The present review traces the history of the development of various AI‑based applications in healthcare and compares AI‑based healthcare with conventional healthcare to show the future prospects for this type of care. Knowledge of the past and present development of AI‑based applications would be useful for the future utilization of novel AI approaches in healthcare.
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📲Channel: @Bioinformatics
📘Journal: Experimental and Therapeutic Medicine (I.F.=2.447)
🗓Publish year: September 2021
💥 Abstract: Artificial intelligence (AI) has been developed through repeated new discoveries since around 1960. The use of AI is now becoming widespread within society and our daily lives. AI is also being introduced into healthcare, such as medicine and drug development; however, it is currently biased towards specific domains. The present review traces the history of the development of various AI‑based applications in healthcare and compares AI‑based healthcare with conventional healthcare to show the future prospects for this type of care. Knowledge of the past and present development of AI‑based applications would be useful for the future utilization of novel AI approaches in healthcare.
📎 Study the paper
📲Channel: @Bioinformatics
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📑 Ten quick tips for machine learning in computational biology
📘Journal: BioData Mining (I.F.=2.522)
🗓Publish year: 2017
💥 Abstract: Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experience to run a data mining project effectively, and therefore can follow incorrect practices, that may lead to common mistakes or over-optimistic results. With this review, we present ten quick tips to take advantage of machine learning in any computational biology context, by avoiding some common errors that we observed hundreds of times in multiple bioinformatics projects. We believe our ten suggestions can strongly help any machine learning practitioner to carry on a successful project in computational biology and related sciences.
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📲Channel: @Bioinformatics
📘Journal: BioData Mining (I.F.=2.522)
🗓Publish year: 2017
💥 Abstract: Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experience to run a data mining project effectively, and therefore can follow incorrect practices, that may lead to common mistakes or over-optimistic results. With this review, we present ten quick tips to take advantage of machine learning in any computational biology context, by avoiding some common errors that we observed hundreds of times in multiple bioinformatics projects. We believe our ten suggestions can strongly help any machine learning practitioner to carry on a successful project in computational biology and related sciences.
📎 Study the paper
📲Channel: @Bioinformatics
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👨💼All about Biological Engineering related jobs
(including Biomedical and Computational Biology occupations)
🌐 Read more
📲Channel: @Bioinformatics
(including Biomedical and Computational Biology occupations)
🌐 Read more
📲Channel: @Bioinformatics
ZDNet
Biological engineering degree jobs: All of your options
A biological engineering degree gives you the opportunity to find jobs in manufacturing, research, and development.
📑 Project-based learning course on metabolic network modelling in computational systems biology
📘Journal: PLOS Computational Biology (I.F.=4.475)
🗓Publish year: 2022
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📲Channel: @Bioinformatics
📘Journal: PLOS Computational Biology (I.F.=4.475)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
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