📑Recent advances in biomedical literature mining
💥The goal of this paper is to provide a review of the recent advances in BLM from biomedical informatics (BMI) and computer science (CS) communities and inspire new research directions.
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📲Channel: @Bioinformatics
💥The goal of this paper is to provide a review of the recent advances in BLM from biomedical informatics (BMI) and computer science (CS) communities and inspire new research directions.
🌐 Study the paper
📲Channel: @Bioinformatics
🎬Free virtual workshop
🧑💻 Exploring biological networks and its application in health and disease
🗓 Date:
08 - 12 November 2021
🕚 Time:
Theory : 13h (62%)
Practical : 8h (38%)
Total : 21h lectures + 2h Virtual Poster Sessions
📍Location: Virtually via Zoom
ℹ️ More information
✍️ Registration
📲Channel: @Bioinformatics
🧑💻 Exploring biological networks and its application in health and disease
🗓 Date:
08 - 12 November 2021
🕚 Time:
Theory : 13h (62%)
Practical : 8h (38%)
Total : 21h lectures + 2h Virtual Poster Sessions
📍Location: Virtually via Zoom
ℹ️ More information
✍️ Registration
📲Channel: @Bioinformatics
🧑💻 1st International Student Biohackathon in Central Asia
💥International Student Biohackathon from Nazarbayev University iGEM focused on solving natural science problems using IT. Our hackathon covers a wide spectrum of problems from data analysis to running simulations based on biological data, we welcome everyone to participate regardless of their specialization or skill level!
🗓 Date: October 10-12
🌐Format: Online, Team based
👯Team size: 2-4 people
✍️ Registration
▫️Deadline: October 7
▫️Individual | Team
▫️Individual applications will be assigned to teams by us
🎖Winners will receive unique merchandise along with a cash prize!
ℹ️ More info: http://code-on.info
📲Channel: @Bioinformatics
💥International Student Biohackathon from Nazarbayev University iGEM focused on solving natural science problems using IT. Our hackathon covers a wide spectrum of problems from data analysis to running simulations based on biological data, we welcome everyone to participate regardless of their specialization or skill level!
🗓 Date: October 10-12
🌐Format: Online, Team based
👯Team size: 2-4 people
✍️ Registration
▫️Deadline: October 7
▫️Individual | Team
▫️Individual applications will be assigned to teams by us
🎖Winners will receive unique merchandise along with a cash prize!
ℹ️ More info: http://code-on.info
📲Channel: @Bioinformatics
👍1
💡New inspiring paper for
Identification of hub genes based on WGCNA
📑 Identification of hub genes in bladder cancer based on weighted gene co-expression network analysis
📲Channel: @Bioinformatics
Identification of hub genes based on WGCNA
📑 Identification of hub genes in bladder cancer based on weighted gene co-expression network analysis
📲Channel: @Bioinformatics
🔖Ten simple rules for
Organizing a bioinformatics training course in low- and middle-income countries
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📲Channel: @Bioinformatics
Organizing a bioinformatics training course in low- and middle-income countries
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📲Channel: @Bioinformatics
📕Cytoscape tutorial:
💥How to add gene expression data to an interaction network
🌐 Watch
🔎Details:
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color of the nodes to represent the changes in gene expression
5. Search for a specific node in the network and create a sub-network from all nodes that interact with this node
6. Change the layout of the network
7. Save the network as an image
8. Save the node or edge table as a .csv file
📲Channel: @Bioinformatics
💥How to add gene expression data to an interaction network
🌐 Watch
🔎Details:
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color of the nodes to represent the changes in gene expression
5. Search for a specific node in the network and create a sub-network from all nodes that interact with this node
6. Change the layout of the network
7. Save the network as an image
8. Save the node or edge table as a .csv file
📲Channel: @Bioinformatics
YouTube
Cytoscape tutorial: How to add gene expression data to an interaction network
Describes how to:
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color of…
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color of…
🧑🏭 Position for MSc or PhD in computational biology, bioinformatics or computer science
💥To apply, please send a motivation leer stating why you would like to join our lab, your CV, and the contact information (or letters of recommendation) of at least two referees to:
Dr. Simona Lodato (simona.lodato@hunimed.eu)
📲Channel: @Bioinformatics
💥To apply, please send a motivation leer stating why you would like to join our lab, your CV, and the contact information (or letters of recommendation) of at least two referees to:
Dr. Simona Lodato (simona.lodato@hunimed.eu)
📲Channel: @Bioinformatics
📑Gene Identification Tools in Bioinformatics
💥One of the most essential aspects of bioinformatics is gene prediction. Gene prediction involves locating regions of genomic DNA that encode genes (protein-coding genes). Gene prediction or gene identification is extremely important because it helps scientists to distinguish between coding and non-coding regions of a genome, explain genes in terms of their function, conduct research related to detection, treatment, and prevention of genetic disorder diseases, etc. Genes are identified broadly via two methods, i.e., a) similarity-based searches and b) Ab-initio prediction. These methods are briefly discussed and related tools introduced.
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📲Channel: @Bioinformatics
💥One of the most essential aspects of bioinformatics is gene prediction. Gene prediction involves locating regions of genomic DNA that encode genes (protein-coding genes). Gene prediction or gene identification is extremely important because it helps scientists to distinguish between coding and non-coding regions of a genome, explain genes in terms of their function, conduct research related to detection, treatment, and prevention of genetic disorder diseases, etc. Genes are identified broadly via two methods, i.e., a) similarity-based searches and b) Ab-initio prediction. These methods are briefly discussed and related tools introduced.
🌐 Study
📲Channel: @Bioinformatics
🎞 A guide to molecular interactions
💥Free recorded webinar
💠Outcomes:
▫️Explain what molecular interactions are
▫️Describe what IntAct can be used for
▫️Search for interaction data
🌐 Watch
📲Channel: @Bioinformatics
💥Free recorded webinar
💠Outcomes:
▫️Explain what molecular interactions are
▫️Describe what IntAct can be used for
▫️Search for interaction data
🌐 Watch
📲Channel: @Bioinformatics
Panopto
A guide to molecular interactions
Zoom Meeting ID: 96843688152
• Host: EMBL-EBI Webinars
• Meeting Start: 05/26/2021 @ 3:08 PM
• Recording Start: 05/26/2021 @ 3:29 PM
• Duration: 1 hr 5 mins
• Host: EMBL-EBI Webinars
• Meeting Start: 05/26/2021 @ 3:08 PM
• Recording Start: 05/26/2021 @ 3:29 PM
• Duration: 1 hr 5 mins
🧑💻Using Web BLAST Effectively
💥from NCBI Virtual Workshop Series
🗓 Date:
2021-10-14 @ 01:00 PM to 2021-10-14 @ 02:30 PM ET
📍Location: Online Event
✍️ Registration (Deadline: 2021-10-01)
ℹ️ More information
📲Channel: @Bioinformatics
💥from NCBI Virtual Workshop Series
🗓 Date:
2021-10-14 @ 01:00 PM to 2021-10-14 @ 02:30 PM ET
📍Location: Online Event
✍️ Registration (Deadline: 2021-10-01)
ℹ️ More information
📲Channel: @Bioinformatics
📽 Notes about pursuing a career in bioinformatics coming from a biology background
🌐 Watch
📲Channel: @Bioinformatics
🌐 Watch
📲Channel: @Bioinformatics
📰A Quick Guide for Building a Successful Bioinformatics Community
From abstract: “Scientific community” refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. ....We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities.
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📲Channel: @Bioinformatics
From abstract: “Scientific community” refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. ....We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities.
🌐Read the article
📲Channel: @Bioinformatics
📄A survey on deep learning in DNA/RNA motif mining
From abstract: DNA/RNA motif mining is the foundation of gene function research. The DNA/RNA motif mining plays an extremely important role in identifying the DNA- or RNA-protein binding site, which helps to understand the mechanism of gene regulation and management. Related algorithms can be divided into two categories: the enumeration approach and the probabilistic method. In recent years, machine learning methods had made great progress, especially the algorithm represented by deep learning had achieved good performance... We introduce the application of deep learning in the field of motif mining in terms of data preprocessing, features of existing deep learning architectures and comparing the differences between the basic deep learning models. ..
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📲Channel: @Bioinformatics
From abstract: DNA/RNA motif mining is the foundation of gene function research. The DNA/RNA motif mining plays an extremely important role in identifying the DNA- or RNA-protein binding site, which helps to understand the mechanism of gene regulation and management. Related algorithms can be divided into two categories: the enumeration approach and the probabilistic method. In recent years, machine learning methods had made great progress, especially the algorithm represented by deep learning had achieved good performance... We introduce the application of deep learning in the field of motif mining in terms of data preprocessing, features of existing deep learning architectures and comparing the differences between the basic deep learning models. ..
🌐 Study the paper
📲Channel: @Bioinformatics
🧑🏭 Bioinformatics position
in Fondazione IRCCS Istituto Nazionale Tumori di Milano Health
📧 Contacts:
To mariopaolo.colombo@istitutotumori.mi.it
Cc claudia.chiodoni@istitutotumori.mi.it; ester.grande@istitutotumori.mi.it
📲Channel: @Bioinformatics
in Fondazione IRCCS Istituto Nazionale Tumori di Milano Health
📧 Contacts:
To mariopaolo.colombo@istitutotumori.mi.it
Cc claudia.chiodoni@istitutotumori.mi.it; ester.grande@istitutotumori.mi.it
📲Channel: @Bioinformatics
💫An Educational Bioinformatics Project to Improve Genome Annotation
From abstract: ... This Hypothetical Protein Characterization Project uses multiple well-documented, freely available, web-based, bioinformatics resources that analyze an amino acid sequence to (1) detect sequence similarities to other proteins, (2) identify domains, (3) predict tertiary structure including active site characterization and potential binding ligands, and (4) determine cellular location....
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📲Channel: @Bioinformatics
From abstract: ... This Hypothetical Protein Characterization Project uses multiple well-documented, freely available, web-based, bioinformatics resources that analyze an amino acid sequence to (1) detect sequence similarities to other proteins, (2) identify domains, (3) predict tertiary structure including active site characterization and potential binding ligands, and (4) determine cellular location....
🌐 Study the article
📲Channel: @Bioinformatics
📚 My Journey Into Data Science and Bioinformatics
▫️Part one: Programming
▫️Part two: Sequencing Crash Course
▫️Part three: Apply parts 1 and 2 to whatever problem that we’re faced with
📲Channel: @Bioinformatics
▫️Part one: Programming
▫️Part two: Sequencing Crash Course
▫️Part three: Apply parts 1 and 2 to whatever problem that we’re faced with
📲Channel: @Bioinformatics