π Online MSc Bioinformatics
π₯Flexible, 100% online study
β° Duration: 2.5 Years
π Start Date: June 2021
βοΈ More information: Click here
π²Channel: @Bioinformatics
π₯Flexible, 100% online study
β° Duration: 2.5 Years
π Start Date: June 2021
βοΈ More information: Click here
π²Channel: @Bioinformatics
π§¬Everything about RNA-Seq
π https://rnaseq.uoregon.edu/
The purpose of this site is to provide a comprehensive discussion of each of the steps that are involved in performing RNA-seq, and to highlight the primary options that are available along with some guidance for choosing between various options. The primary content is topically organized according to the work-flow of a typical RNA-seq experiment.
π²Channel: @Bioinformatics
π https://rnaseq.uoregon.edu/
The purpose of this site is to provide a comprehensive discussion of each of the steps that are involved in performing RNA-seq, and to highlight the primary options that are available along with some guidance for choosing between various options. The primary content is topically organized according to the work-flow of a typical RNA-seq experiment.
π²Channel: @Bioinformatics
π1
π§Ύ Computational network biology: Data, models, and
applications
A review paper from Physics Reports (IF=25.79)
https://doc.rero.ch/record/328505/files/zha_cnb.pdf
Biological entities are involved in intricate and complex interactions, in which uncovering the biological information from the network concepts are of great significance. Benefiting from the advances of network science and high-throughput biomedical technologies, studying the biological systems from network biology has attracted much attention in recent years, and networks have long been central to our understanding of biological systems, in the form of linkage maps among genotypes, phenotypes, and the corresponding environmental factors. In this review, we summarize the recent developments of computational network biology, first introducing various types of biological networks and network structural properties. We then review the network-based approaches, ranging from some network metrics to the complicated machine-learning methods, and emphasize how to use these algorithms to gain new biological insights. Furthermore, we highlight the application in neuroscience, human disease, and drug developments from the perspectives of network science, and we discuss some major challenges and future directions. We hope that this review will draw increasing interdisciplinary attention from physicists, computer scientists, and biologists.
π²Channel: @Bioinformatics
applications
A review paper from Physics Reports (IF=25.79)
https://doc.rero.ch/record/328505/files/zha_cnb.pdf
Biological entities are involved in intricate and complex interactions, in which uncovering the biological information from the network concepts are of great significance. Benefiting from the advances of network science and high-throughput biomedical technologies, studying the biological systems from network biology has attracted much attention in recent years, and networks have long been central to our understanding of biological systems, in the form of linkage maps among genotypes, phenotypes, and the corresponding environmental factors. In this review, we summarize the recent developments of computational network biology, first introducing various types of biological networks and network structural properties. We then review the network-based approaches, ranging from some network metrics to the complicated machine-learning methods, and emphasize how to use these algorithms to gain new biological insights. Furthermore, we highlight the application in neuroscience, human disease, and drug developments from the perspectives of network science, and we discuss some major challenges and future directions. We hope that this review will draw increasing interdisciplinary attention from physicists, computer scientists, and biologists.
π²Channel: @Bioinformatics
π¦· Antibody May Be Able to Regenerate Missing Teeth
π News detail
https://www.kyoto-u.ac.jp/en/research-news/2021-03-31
π Publication information:
https://doi.org/10.1126/sciadv.abf1798
π²Channel: @Bioinformatics
π News detail
https://www.kyoto-u.ac.jp/en/research-news/2021-03-31
π Publication information:
https://doi.org/10.1126/sciadv.abf1798
π²Channel: @Bioinformatics
KYOTO UNIVERSITY
New drug to regenerate lost teeth
Japan -- The tooth fairy is a welcome guest for any child who has lost a tooth. Not only will the fairy leave a small gift under the pillow, but the child can be assured of a new tooth in a few months. The same cannot be said of adults who have lost theirβ¦
π Introduction to Machine Learning on Biomedical Data
β«οΈFree recorded Online Course
β«οΈVideo+Required files
The course will begin with a very brief overview of the mathematical foundations of ML, specifically linear regression, logistic regression, and multilayer perceptrons. Applying these models to the well-studied dataset of hand written digits, MNIST, weβll gain first-hand experience with model selection, training and validation. We will then introduce several abstractions from...
π Course link
π²Channel: @Bioinformatics
β«οΈFree recorded Online Course
β«οΈVideo+Required files
The course will begin with a very brief overview of the mathematical foundations of ML, specifically linear regression, logistic regression, and multilayer perceptrons. Applying these models to the well-studied dataset of hand written digits, MNIST, weβll gain first-hand experience with model selection, training and validation. We will then introduce several abstractions from...
π Course link
π²Channel: @Bioinformatics
π¬ Can one mRNA molecule be a template for multiple proteins in eukaryotes?
πΉ https://phys.org/news/2021-02-video-green-algae-reveals-mrna.html
πResearch link:
DOI: 10.1073/pnas.2017714118
π²Channel: @Bioinformatics
πΉ https://phys.org/news/2021-02-video-green-algae-reveals-mrna.html
πResearch link:
DOI: 10.1073/pnas.2017714118
π²Channel: @Bioinformatics
phys.org
Video: Green algae reveals that one mRNA encodes many proteins
Gene expression in eukaryotes was long held to be monocistronicβthat is, a single gene makes messenger RNA, which encodes a single protein. Recently reported in the Proceedings of the National Academy ...
π§βπ¬Systematic review of computational methods for predicting long noncoding RNAs
New paper from Briefings in Functional Genomics journal
π https://doi.org/10.1093/bfgp/elab016
πFrom Abstract:
Long non-coding RNAs are a type of RNA, defined as being transcripts with lengths exceeding 200 nucleotides that are not translated into protein. In recent years, many computational methods have been developed to predict lncRNAs from transcripts, but there is no systematic review on these computational methods. In this review, authors introduce databases and features involved in the development of computational prediction models, and subsequently summarize existing state-of-the-art computational methods, including methods based on binary classifiers, deep learning and ensemble learning. However, a user-friendly way of employing existing state-of-the-art computational methods is in demand. Therefore, they develop a Python package ezLncPred, which provides a pragmatic command line implementation to utilize nine state-of-the-art lncRNA prediction methods. Finally, we discuss challenges of lncRNA prediction and future directions.
π²Channel: @Bioinformatics
New paper from Briefings in Functional Genomics journal
π https://doi.org/10.1093/bfgp/elab016
πFrom Abstract:
Long non-coding RNAs are a type of RNA, defined as being transcripts with lengths exceeding 200 nucleotides that are not translated into protein. In recent years, many computational methods have been developed to predict lncRNAs from transcripts, but there is no systematic review on these computational methods. In this review, authors introduce databases and features involved in the development of computational prediction models, and subsequently summarize existing state-of-the-art computational methods, including methods based on binary classifiers, deep learning and ensemble learning. However, a user-friendly way of employing existing state-of-the-art computational methods is in demand. Therefore, they develop a Python package ezLncPred, which provides a pragmatic command line implementation to utilize nine state-of-the-art lncRNA prediction methods. Finally, we discuss challenges of lncRNA prediction and future directions.
π²Channel: @Bioinformatics
OUP Academic
systematic review of computational methods for predicting long noncoding RNAs
Abstract. Accurately and rapidly distinguishing long noncoding RNAs (lncRNAs) from transcripts is prerequisite for exploring their biological functions. In rece
π¨βπ« Microbial Community Analysis Workshop
πFree and Virtual
π May 18-27, 2021
π₯Topics:
The workshop will cover best practices in bioinformatics analysis of amplicon-based microbial community data β using a 16S rRNA data set. Participants will learn to retrieve sequence data from the NCBI Sequence Read Archive (SRA), and will then use a BASH command-line environment on the Biomix computational cluster to perform sequence analysis. R will be used to perform downstream analysis and visualization of those data. Compositional statistical methods will be introduced and used throughout.
βοΈ Register here
Seats are limited
βΉοΈ More information:
https://bioinformatics.udel.edu/core/mcaw-2021/
π²Channel: @Bioinformatics
πFree and Virtual
π May 18-27, 2021
π₯Topics:
The workshop will cover best practices in bioinformatics analysis of amplicon-based microbial community data β using a 16S rRNA data set. Participants will learn to retrieve sequence data from the NCBI Sequence Read Archive (SRA), and will then use a BASH command-line environment on the Biomix computational cluster to perform sequence analysis. R will be used to perform downstream analysis and visualization of those data. Compositional statistical methods will be introduced and used throughout.
βοΈ Register here
Seats are limited
βΉοΈ More information:
https://bioinformatics.udel.edu/core/mcaw-2021/
π²Channel: @Bioinformatics
π¨βπ« Vacancy
Tenure track 'Group leader translational tumor bioinformatics'
β Tasks:
-Development of innovative technologies and bioinformatics for tumor diagnostics in close collaboration with laboratory specialists.
-Development of a research line in tumor bioinformatics.
-Academic supervision of bioinformaticians responsible for the implementation of innovative tumor diagnostics.
-Development of research collaborations with related research groups
βΉοΈ Click here for More information
π²Channel: @Bioinformatics
Tenure track 'Group leader translational tumor bioinformatics'
β Tasks:
-Development of innovative technologies and bioinformatics for tumor diagnostics in close collaboration with laboratory specialists.
-Development of a research line in tumor bioinformatics.
-Academic supervision of bioinformaticians responsible for the implementation of innovative tumor diagnostics.
-Development of research collaborations with related research groups
βΉοΈ Click here for More information
π²Channel: @Bioinformatics
π₯ Fantastic databases and where to find them: Web applications for researchers in a rush
π https://www.scielo.br/scielo.php?pid=S1415-47572021000300801&script=sci_arttext
from Abstract
Here, we present an overview of human databases with web applications. The databases and tools allow the search of biological sequences, genes and genomes, gene expression patterns, epigenetic variation, protein-protein interactions, variant frequency, regulatory elements, and comparative analysis between human and model organisms. The goal is to provide an opportunity for exploring large datasets and analyzing the data for users with little or no programming skills. Public user-friendly web-based databases facilitate data mining and the search for information applicable to healthcare professionals. To show the databases at work, we present a case study using ACE2 as example of a gene to be investigated. The analysis and the complete list of databases is available in the paper.
π²Channel: @Bioinformatics
π https://www.scielo.br/scielo.php?pid=S1415-47572021000300801&script=sci_arttext
from Abstract
Here, we present an overview of human databases with web applications. The databases and tools allow the search of biological sequences, genes and genomes, gene expression patterns, epigenetic variation, protein-protein interactions, variant frequency, regulatory elements, and comparative analysis between human and model organisms. The goal is to provide an opportunity for exploring large datasets and analyzing the data for users with little or no programming skills. Public user-friendly web-based databases facilitate data mining and the search for information applicable to healthcare professionals. To show the databases at work, we present a case study using ACE2 as example of a gene to be investigated. The analysis and the complete list of databases is available in the paper.
π²Channel: @Bioinformatics
πΆ Human placentas routinely consist of a quilt of different genotypes, and this strange heterogeneity may actually play a role in protecting the fetus from genetic harm
πhttps://www.quantamagazine.org/new-genomic-study-of-placenta-finds-deep-links-to-cancer-20210408
π Main research link
π²Channel: @Bioinformatics
πhttps://www.quantamagazine.org/new-genomic-study-of-placenta-finds-deep-links-to-cancer-20210408
π Main research link
π²Channel: @Bioinformatics
Quanta Magazine
New Genomic Study of Placenta Finds Deep Links to Cancer
A patchwork of genomic differences in the placenta may explain the organβs βlive fast, die youngβ strategy and its connections to cancer.
Free Online Book for
πBiomedical Data Science
πhttp://genomicsclass.github.io/book/
Channel: @Bioinformatics
πBiomedical Data Science
πhttp://genomicsclass.github.io/book/
Channel: @Bioinformatics
π§βπ«*NGS Data Analysis Workshop*
Learn the most demanded skill in Bioinformatics without the need to code!!
β± *When :* 19 - 22 April | 6:30 to 8:30 PM IST
π΅ *Fee :* Rs 1000 for Indian Nationals | USD 20 for Foreign Nationals
β All sessions will be conducted on Zoom
β Recording for each session will be shared with the participants
β E-Certificate will be provided to all the participants
βΉοΈ Click here to know more and register
π²Channel: @Bioinformatics
Learn the most demanded skill in Bioinformatics without the need to code!!
β± *When :* 19 - 22 April | 6:30 to 8:30 PM IST
π΅ *Fee :* Rs 1000 for Indian Nationals | USD 20 for Foreign Nationals
β All sessions will be conducted on Zoom
β Recording for each session will be shared with the participants
β E-Certificate will be provided to all the participants
βΉοΈ Click here to know more and register
π²Channel: @Bioinformatics
π€ Finding Cancer causing genes without mutation signature!
https://www.news-medical.net/news/20210413/New-algorithm-can-predict-which-genes-cause-cancer.aspx
π²Channel: @Bioinformatics
https://www.news-medical.net/news/20210413/New-algorithm-can-predict-which-genes-cause-cancer.aspx
π²Channel: @Bioinformatics
News-Medical.net
New algorithm can predict which genes cause cancer
A new algorithm can predict which genes cause cancer, even if their DNA sequence is not changed. A team of researchers in Berlin combined a wide variety of data, analyzed it with "Artificial Intelligence" and identified numerous cancer genes.
π1
π₯ Building the learning ecosystem of health:
from data tracking to preventive medicine
https://www.youtube.com/watch?v=0oHGSeC25Pk
share your ideas at the ELIXIR Innovation and SME Forum, organized on 13 September 2021 as part of the BC2 Basel Computational Biology Conference.
β³ Abstract submission deadline: 16 April
βΉοΈ More information: https://www.bc2.ch/elixir-forumβ
π²Channel: @Bioinformatics
from data tracking to preventive medicine
https://www.youtube.com/watch?v=0oHGSeC25Pk
share your ideas at the ELIXIR Innovation and SME Forum, organized on 13 September 2021 as part of the BC2 Basel Computational Biology Conference.
β³ Abstract submission deadline: 16 April
βΉοΈ More information: https://www.bc2.ch/elixir-forumβ
π²Channel: @Bioinformatics
YouTube
Submit your abstract to the ELIXIR Innovation and SME Forum by 16 April
βBuilding the learning ecosystem of health: from data tracking to preventive medicineβ: share your ideas at the ELIXIR Innovation and SME Forum, organized on 13 September 2021 as part of the BC2 Basel Computational Biology Conference.
Abstract submissionβ¦
Abstract submissionβ¦
π·A novel, quick, and easy system for genetic analysis of SARS-CoV-2
https://phys.org/news/2021-04-quick-easy-genetic-analysis-sars-cov-.html
π² Channel: @Bioinformatics
https://phys.org/news/2021-04-quick-easy-genetic-analysis-sars-cov-.html
π² Channel: @Bioinformatics
phys.org
A novel, quick, and easy system for genetic analysis of SARS-CoV-2
Researchers from Osaka University and Hokkaido University develop a system for analyzing mutations in SARS-CoV-2 that is much simpler and faster than existing methods.
π½ Sharing biological data: why, when, and how
https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.14067
π₯Here, you can see good practices to make your biological data publicly accessible and usable, generally and for several specific kinds of data.
π² Channel: @Bioinformatics
https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.14067
π₯Here, you can see good practices to make your biological data publicly accessible and usable, generally and for several specific kinds of data.
π² Channel: @Bioinformatics
π1
π Data Analysis and Visualization in R
These online lessons below were designed for those interested in working with genomics data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R
πhttps://datacarpentry.org/R-genomics
π²Channel: @Bioinformatics
These online lessons below were designed for those interested in working with genomics data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R
πhttps://datacarpentry.org/R-genomics
π²Channel: @Bioinformatics
π Biden Administration Announces $1.7 Billion Investment for Genomics and Bioinformatics to Fight COVID-19 Variants
https://www.whitehouse.gov/briefing-room/statements-releases/2021/04/16/fact-sheet-biden-administration-announces-1-7-billion-investment-to-fight-covid-19-variants/
π² Channel: @Bioinformatics
https://www.whitehouse.gov/briefing-room/statements-releases/2021/04/16/fact-sheet-biden-administration-announces-1-7-billion-investment-to-fight-covid-19-variants/
π² Channel: @Bioinformatics
The White House
Fact Sheet: Biden Administration Announces $1.7 Billion Investment to Fight COVID-β 19 Variants
Funding from American Rescue Plan will help CDC and Governors monitor, track, and defeat emerging variants that are currently threatening pockets of the
π¬Sample Bioinformatics Analysis
https://www.hindawi.com/journals/cmmm/2021/5550407/
π²Channel: @Bioinformatics
https://www.hindawi.com/journals/cmmm/2021/5550407/
π²Channel: @Bioinformatics
Hindawi
Lung adenocarcinoma (LUAD) is one of the malignant lung tumors. However, its pathology has not been fully understood. The purposeβ¦
Identification of Hub Genes Associated with Lung Adenocarcinoma Based on Bioinformatics Analysis
π©βπ» Sample practical research of genome-wide association study using microarray gene expression
https://www.sciencedirect.com/science/article/pii/S1319562X21002825
π²Channel: @Bioinformatics
https://www.sciencedirect.com/science/article/pii/S1319562X21002825
π²Channel: @Bioinformatics