Address of the bookmark: https://github.com/legumeinfo/gcv

Features

• Circular and linear views of genomes

• Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs

• Smooth zooming down to the sequence level

• Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)

• Save high resolution PNG maps up to 8000x8000px

• Fully documented API for interacting with CGView.js maps

Address of the bookmark: https://js.cgview.ca/

What Are lncRNAs?

lncRNAs are RNA transcripts longer than 200 nucleotides that do not code for proteins. Despite their non-coding nature, they play diverse roles in gene regulation, including chromatin remodeling, transcriptional control, and post-transcriptional processing. Unlike messenger RNAs (mRNAs), lncRNAs often function as scaffolds, decoys, or guides in cellular machinery, influencing biological processes such as cell differentiation, immune response, and even cancer metastasis.

Challenges in lncRNA Research

Identifying and understanding lncRNAs pose unique challenges:

1. High Sequence Variability: Unlike protein-coding genes, lncRNAs exhibit low sequence conservation across species, making functional predictions difficult.
2. Low Expression Levels: lncRNAs are often expressed at low levels, complicating their detection in transcriptomic data.
3. Diverse Functions: The multifunctional nature of lncRNAs requires advanced computational tools to decipher their roles in complex networks.

Bioinformatics: A Crucial Ally in lncRNA Research

Bioinformatics bridges the gap between raw biological data and meaningful insights, making it indispensable in lncRNA research. Here’s how:

1. Identification and Annotation

High-throughput sequencing technologies like RNA-seq generate vast amounts of data. Bioinformatics tools such as StringTie, Cufflinks, and HISAT2 help assemble and annotate lncRNAs from this data. Additionally, databases like NONCODE, LNCipedia, and Ensembl provide curated repositories of lncRNA sequences and annotations.

2. Functional Prediction

Bioinformatics algorithms predict the potential functions of lncRNAs by analyzing their interactions with DNA, RNA, and proteins. Tools like LncRNA2Function and RIblast utilize sequence motifs and secondary structure predictions to hypothesize about the roles of specific lncRNAs.

3. Network Construction

lncRNAs often act as regulatory hubs. Bioinformatics platforms such as Cytoscape enable the visualization of lncRNA-mediated networks, elucidating their roles in pathways like cell cycle regulation and apoptosis.

4. Epigenetic Studies

lncRNAs are known to interact with chromatin-modifying complexes, influencing gene expression epigenetically. Tools like ChIP-seq and ATAC-seq, combined with computational pipelines, identify these interactions and map them to the genome.

5. Clinical Applications

Bioinformatics aids in the discovery of lncRNA biomarkers for diseases like cancer and neurodegenerative disorders. Machine learning models analyze differential expression profiles, helping prioritize lncRNAs with therapeutic potential.

Case Study: lncRNAs in Cancer Research

lncRNAs such as HOTAIR and MALAT1 have been implicated in cancer progression. Bioinformatics analyses have revealed their roles in promoting metastasis and altering the tumor microenvironment. For example, transcriptome analysis in cancer patients identifies lncRNA expression signatures, enabling precision medicine approaches.

Future Directions

The fusion of bioinformatics with experimental biology is unlocking the secrets of lncRNAs. Advances in artificial intelligence, single-cell sequencing, and structural modeling promise to overcome current limitations. Here are some promising directions:

• Integrative Analysis: Combining multi-omics data to understand the interplay of lncRNAs with other biomolecules.
• CRISPR Screens: Leveraging bioinformatics to design CRISPR-based functional screens for lncRNAs.
• Therapeutic Development: Using bioinformatics to design lncRNA-based therapeutics, including antisense oligonucleotides and RNA interference tools.

Conclusion

lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing our approach to complex diseases.

The journey into the world of lncRNAs is only beginning, and bioinformatics will continue to play a pivotal role in decoding these molecular mysteries. Whether you’re a researcher, clinician, or bioinformatics enthusiast, the study of lncRNAs offers a fascinating frontier of discovery.

Overview of SLiM and msprime

SLiM: Forward Genetic Simulator

SLiM is a free, open-source tool designed for forward genetic simulations. It allows researchers to model complex evolutionary scenarios, including selection, recombination, and demographic events, making it particularly useful for studying adaptation and selection in populations.

Key Features of SLiM:

• Simulates population evolution forward in time

• Supports custom evolutionary models using an embedded scripting language

• Allows modeling of spatial and ecological dynamics

• Provides high flexibility and extensibility for user-defined scenarios

• Available on GitHub as an open-source project

msprime: Ancestry and Mutation Simulator

msprime is an efficient, open-source tool that simulates ancestry and mutations using a coalescent framework. It is known for its high-speed performance and low memory requirements, making it a popular choice for large-scale genomic simulations.

Key Features of msprime:

• Implements coalescent simulations for ancestry modeling

• Efficiently simulates large population histories

• Supports the addition of mutations to genealogies

• Developed using an open-source community model

• Often faster and more memory-efficient than alternative simulators

Using SLiM and msprime with slendr

Both SLiM and msprime can be integrated with slendr, a framework that facilitates structured population genetic simulations. This integration allows for seamless comparison of simulation outputs.

How They Work Together:

• SLiM and msprime simulations can be analyzed within slendr.

• The ts_read() function in slendr enables loading and comparing tree sequence outputs from both simulators.

• This integration allows researchers to validate simulation results and gain deeper insights into evolutionary processes.

Performance Considerations

While SLiM offers powerful forward simulations with extensive customization, msprime is often preferred for its speed and memory efficiency when simulating ancestry and mutations. The choice between the two depends on the research goals:

• For detailed evolutionary modeling with selection and recombination: Use SLiM.

• For large-scale coalescent simulations with mutations: Use msprime.

• For comparing different simulation models and their outputs: Use slendr to integrate SLiM and msprime results.

Conclusion

SLiM and msprime are valuable tools for genome simulation, each serving distinct but complementary purposes in population genetics research. By leveraging the strengths of both simulators with slendr, researchers can conduct robust and efficient evolutionary simulations, enhancing our understanding of genetic diversity and adaptation.

For more information, check out the official GitHub repositories for SLiM and msprime, and explore the slendr framework for streamlined simulation workflow

Tivicay is indicated for infected adults, both treatment-naive and treatment-experienced, including those treated with other integrase strand transfer inhibitors; as well as for children aged 12 years and older weighing at least 40 kg (approx. 88 lbs). The drug - which was used without a pharmacokinetic boosting agent - interferes with one of the enzymes necessary for HIV to multiply, and can be taken with or without food and at any time of day.

http://www.fda.gov/ForConsumers/ByAudience/ForPatientAdvocates/HIVandAIDSActivities/ucm364869.htm

sudo /etc/init.d/apache2 stop

sudo /etc/init.d/mysql stop

sudo /etc/init.d/proftpd stop

sudo /opt/lampp/lampp start

PhpMyAdmin “Wrong permissions on configuration file, should not be world writable!”

Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:

Just chmod 0755 the file

sudo chmod 0755 config.inc.php

Address of the bookmark: https://reactome.org/

To fully leverage these opportunities, bioinformaticians require specialized tools and databases. This blog highlights essential resources for mycology research, focusing on databases, tools, and platforms tailored for fungal biology.

1. Fungal Databases

1.1. MycoCosm

Website: MycoCosm
Developed by the DOE Joint Genome Institute, MycoCosm is a comprehensive portal for fungal genomics. It offers genomic and transcriptomic data for a wide range of fungi, including saprobes, pathogens, and symbionts.

• Key Features: Genome browsers, comparative genomics tools, and functional annotations.
• Best For: Large-scale studies on fungal evolution and ecology.

1.2. FungiDB

Website: FungiDB
FungiDB is an integrated genomic resource for fungal pathogens and non-pathogens. It provides access to genome sequences, transcriptomic data, and functional annotations.

• Key Features: Advanced search options, BLAST, and pathway analysis tools.
• Best For: Studying fungal pathogenesis and host-pathogen interactions.

1.3. Index Fungorum

Website: Index Fungorum
This nomenclatural database provides information on the scientific names of fungi. It’s an essential resource for taxonomists and researchers focused on fungal biodiversity.

• Key Features: Taxonomic hierarchy and synonymy tracking.
• Best For: Identifying and classifying fungal species.

1.4. UNITE

Website: UNITE
UNITE is a specialized database for fungal ITS (Internal Transcribed Spacer) sequences, often used in fungal identification and phylogenetics.

• Key Features: Curated reference datasets and community annotations.
• Best For: Environmental mycology and microbial ecology studies.

2. Analytical Tools

2.1. Funannotate

Repository: GitHub - Funannotate
Funannotate is a genome annotation tool designed for fungi. It supports tasks like gene prediction, functional annotation, and orthology analysis.

• Best For: Annotating newly sequenced fungal genomes.

2.2. BUSCO (Benchmarking Universal Single-Copy Orthologs)

Website: BUSCO
BUSCO evaluates genome assembly and annotation completeness using orthologs. It includes a fungal-specific dataset.

• Best For: Assessing the quality of fungal genome assemblies.

2.3. Pathogen-Host Interactions Database (PHI-base)

Website: PHI-base
PHI-base is a manually curated resource containing information on pathogen-host interactions, including fungal pathogens.

• Best For: Exploring virulence factors and host-pathogen relationships.

3. Visualization Platforms

3.1. Cytoscape

Website: Cytoscape
A powerful tool for visualizing molecular interaction networks, Cytoscape can be used to study protein-protein interactions, gene networks, and metabolic pathways in fungi.

• Best For: Network biology and functional genomics.

3.2. iTOL (Interactive Tree of Life)

Website: iTOL
iTOL is an interactive tool for visualizing phylogenetic trees.

• Best For: Displaying fungal phylogenies and comparing evolutionary relationships.

4. Community Resources

4.1. Mycological Society of America (MSA)

Website: MSA
The MSA promotes fungal research and provides access to resources, conferences, and publications.

• Best For: Networking with fungal researchers and accessing recent studies.

4.2. OpenFungi

Website: OpenFungi
OpenFungi is an open-source initiative providing fungal genomic and transcriptomic datasets for research and education.

• Best For: Sharing and accessing public fungal datasets.

5. Genomics Workflows

5.1. Galaxy

Website: Galaxy Project
Galaxy offers a web-based platform for reproducible bioinformatics workflows, including tools for fungal genome and transcriptome analysis.

• Best For: User-friendly analysis pipelines without requiring coding skills.

5.2. Snakemake

Repository: Snakemake
A flexible pipeline management tool that supports fungal data processing and analysis.

• Best For: Custom workflows for large-scale fungal datasets.

Conclusion

Fungal research is a rapidly growing field with vast implications for medicine, agriculture, and industry. For bioinformaticians, the availability of specialized resources—databases, tools, and community platforms—opens doors to innovative discoveries. Whether you are investigating fungal genomics, studying host-pathogen interactions, or exploring fungal biodiversity, the resources outlined above will empower your research journey.

Dive into these resources and help unravel the mysteries of the fungal kingdom!

Deadline: 30.09.2019

Requirement:
Microsoft SQL Server: Administration, Transact-SQL
Machine Learning
Know Deutsch und Englisch langauge

The changes in nr preserve the taxonomic diversity of the entries in the database while reducing the number of titles for identical sequences. GenPept accessions are still accessible via www.ncbi.nlm.nih.gov/protein/$GENBANK_ACCESSION or the IPG website https://www.ncbi.nlm.nih.gov/ipg/.

The "Identical Proteins" link in the alignments section of the webBLAST results takes you to a full list of all accessions associated with a sequence.

For BLAST+ users downloading nr_v5: the database is now approximately 50% smaller, resulting in faster downloads and BLAST searches, and smaller disk space requirements. The database is downloadable at:  ftp://ftp.ncbi.nlm.nih.gov/blast/db/v5/

For BLAST+ there is a cleanup script to help you manage the transition to this smaller database. The script removes unused database volumes: ftp://ftp.ncbi.nlm.nih.gov/blast/temp/cleanup-blastdb-volumes.py

Here are the new rules on how we keep titles in nr_v5:

1.    We keep all refseq, swissprot, pir and PDB titles.

2.    We keep any GenPept titles with a TAXID that has not already been seen in the record.

3.    We keep at least five GenPept titles regardless of whether the TAXIDS have been seen before or not in this record.