BOL: Related items

UCSC SARS-CoV-2 Genome Browser

Jit — Thu, 06 Jan 2022 06:48:40 -0600

The UCSC SARS-CoV-2 Genome Browser (https://genome.ucsc.edu/covid19.html) is an adaptation of our popular genome-browser visualization tool for this virus, containing many annotation tracks and new features, including conservation with similar viruses, immune epitopes, RT–PCR and sequencing primers and CRISPR guides. We invite all investigators to contribute to this resource to accelerate research and development activities globally.

Address of the bookmark: https://www.nature.com/articles/s41588-020-0700-8

MUM&Co is a simple bash script that uses Whole Genome Alignment information provided by MUMmer (v4) to detect variants.

Rahul Nayak — Wed, 27 Apr 2022 04:34:12 -0500

MUM&Co is able to detect:
Deletions, insertions, tandem duplications and tandem contractions (>=50bp & <=150kb)
Inversions (>=1kb) and translocations (>=10kb)

Address of the bookmark: https://github.com/SAMtoBAM/MUMandCo

The ATCC Genome Portal

Abhi — Wed, 15 May 2024 14:24:16 -0500

The ATCC Genome Portal (AGP, https://genomes.atcc.org/) is a database of authenticated genomes for bacteria, fungi, protists, and viruses held in ATCC’s biorepository. It now includes 3,938 assemblies (253% increase) produced under ISO 9000 by ATCC. Here, we present new features and content added to the AGP for the research community.

Address of the bookmark: https://genomes.atcc.org/

Proksee

LEGE — Wed, 27 Mar 2024 11:11:54 -0500

Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.

Please Cite the Following

Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, and Stothard P

Proksee: in-depth characterization and visualization of bacterial genomes

Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326

Address of the bookmark: https://proksee.ca/

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

BioStar — Mon, 05 Aug 2024 23:01:29 -0500

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

Using state of the art tools, easily extended for other viruses
Tool and database updates for critical components via Conda
Built using modern design patterns with Conda and Snakemake
Extensible and easy to customize
Submission Ready Genomes
Customizable reporting with comprehensive visualization

https://ikim-essen.github.io/uncovar/

Github https://github.com/IKIM-Essen/uncovar

Address of the bookmark: https://ikim-essen.github.io/uncovar/

NVIDIA and Arc Institute Unveil Evo 2: A Breakthrough AI for DNA Design

BioStar — Fri, 21 Feb 2025 10:39:47 -0600

NVIDIA and the Arc Institute have introduced Evo 2, a groundbreaking AI model designed to understand, predict, and generate DNA sequences. This marks a major advancement in computational biology, offering scientists an unprecedented tool to decode the genetic blueprint of life and even design entirely new biological systems.

The Power of Evo 2: AI Meets DNA

Evo 2 is the largest AI model for biology ever created, trained on an astonishing 9.3 trillion DNA "letters" (nucleotides) carefully selected from genomes spanning the entire tree of life. This massive dataset ensures that Evo 2 can recognize patterns and relationships in genetic sequences at an unparalleled scale.

For the first time, scientists can design DNA with AI, moving beyond simple sequence analysis to active DNA generation. Evo 2 enables researchers to predict, modify, and even create entire genetic sequences, opening new possibilities in medicine, agriculture, and synthetic biology.

Decoding the Dark Genome

One of the biggest challenges in genetics is understanding the non-coding regions of DNA—vast stretches of the genome that do not code for proteins but play crucial roles in regulating gene expression. These regions control when and how genes are activated, influencing everything from development to disease.

Evo 2 is designed to decode these non-coding elements, helping researchers uncover their functions and use this knowledge to develop gene-based therapies, synthetic life forms, and precision agriculture solutions.

From Reading DNA to Writing It

To put Evo 2’s impact into perspective:

Previous AI models could "read" DNA like a book, analyzing genetic sequences and identifying patterns.
Evo 2 can "write" entirely new DNA, designing functional genes, chromosomes, and even full genomes from scratch.

This means scientists can now engineer biological systems with AI, designing new proteins, metabolic pathways, and genetic circuits to address real-world challenges.

A Step Toward Generative Biology

The Arc Institute describes Evo 2 as a major step toward "generative biology"—a revolutionary approach where AI is used to create novel biological structures rather than just analyzing existing ones. This could lead to breakthroughs such as:

New medicines: AI-generated enzymes and proteins tailored for targeted therapies.
Disease-resistant crops: Genetically optimized plants for higher yield and climate resilience.
Synthetic organisms: Custom-designed microbes for bioremediation, biofuel production, and industrial applications.

An Open-Source Revolution

Unlike many proprietary AI models, Evo 2 is open source, making its capabilities accessible to researchers worldwide. This democratization of AI-driven biology means that scientists from different disciplines can collaborate, experiment, and innovate, accelerating discoveries in genetic engineering and synthetic biology.

With Evo 2, the boundaries of what’s possible in DNA design, genetic engineering, and biological innovation are being redrawn. The future of life sciences is no longer just about understanding life’s code—it’s about writing it.

Narcis Fernandez-Fuentes Lab

Mon, 25 May 2015 07:30:00 -0500

Welcome to our web-site compiling all the research-related activities of the group. Our research interests relate to a number of areas within Bioinformatics. We have a long-standing interest in protein structure prediction and structure-to-function relationships. We work in the study of biomolecular interactions, modeling of protein complexes, the study and characterization of protein-protein interactions, peptide design, modeling of genetic variation, structure-based protein design and different aspects of Plant Bioinformatics. Take a look at the our databases and servers and the list of publications for more information.

More at http://www.bioinsilico.org/

JPred4: A Protein Secondary Structure Prediction Server

Poonam Mahapatra — Fri, 29 Dec 2017 16:14:28 -0600

JPred4 (http://www.compbio.dundee.ac.uk/jpred4) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction.

Address of the bookmark: http://www.compbio.dundee.ac.uk/jpred4/

Installing ELGG on Ubuntu !

Jit — Thu, 25 Nov 2021 01:45:59 -0600

Follow this:

Settings file

Error

Your web server does not have permission to create the settings.php file in your installation directory. You have two choices:

1. Change the permissions on the elgg-config directory of your Elgg installation

2. Copy the file elgg-config/settings.example.php to elgg-config/settings.php and follow the instructions in it for setting your database parameters.

To resolve this --

Change the permision

chmod 777 elgg-config

Web server

Warning

Your server does not support automatic testing of the rewrite rules and your browser does not support checking via JavaScript. You can continue the installation, but you may experience problems with your site. You can manually test the rewrite rules by clicking this link: test. You will see the word success if the rules are working.

create a .httaccess

and provide detail in it

Installation of Elgg

(Note: Elgg requires installing an instance of MySQL.)

Steps to make adjustment and disposal of trial installations easier.

MySQL

At this point, we assume you've set up your MySQL database

Start your mysqld server daemon.
(For the sake of this example, we'll assume we're running on port 9999; you shouldn't actually use this port because only one daemon can run on any port number.)
Login to the server as root user, using the mysql client.
Create a database to store Elgg's tables. We'll call the database elggalpha.
mysql> create database elggalpha;

Grant access to a user — for this example we'll call him/her elggalphauser.

mysql> grant all privileges on elggalpha.* to 'elggalphauser'@'moxie'
    -> identified by 'secretpassword';

Elgg

Type umask 022
Change into your public_html directory (aka folder).
cd public_html
make a directory called elgg
mkdir elgg
Change into the elgg subdirectory of public_html.
cd elgg
download elgg into this directory
you'll end up with a file named
/home/your-user-id/public_html/elgg/elgg-X.X.X.X.zip
(It's not literally X.X.X.X, it might be elgg-1.8.0.1.zip, for example.)
unzip elgg
unzip -q elgg-1.8.0.1.zip
you'll end up with a directory (folder) named
/home/your-user-id/public_html/elgg/elgg-X.X.X.X
make a symbolic link (aka shortcut) to this
ln -s elgg-X.X.X.X alpha
(For example, ln -s elgg-1.8.0.1 alpha)
Give user nobody access to this directory
/usr/misc/bin/acl.sh -r -u nobody elgg-1.8.0.1
create a data directory for elgg (get into your home directory first):
```
cd
mkdir -p elgg/alpha/data
chmod -R 755 elgg/alpha/data
```
Change into the elgg/alpha directory.
cd elgg/alpha
Give user nobody access to this subdirectory data
/usr/misc/bin/acl.sh -u nobody data

In your browser, navigate to your elgg installation
http://moxie.cs.oswego.edu/~your-user-id/elgg/alpha/
You'll have a screen which includes this message:

Welcome

Installing Elgg has 6 simple steps and reading this welcome is the first one!

If you haven't already, read through the installation instructions included with Elgg (or click the instructions link at the bottom of the page).

If you are ready to proceed, click the Next button.

Follow configuration process:

The first screen probably will contain a success message in green and a failure message in pink:
```
Requirements check

Your server failed the requirements check. After you have fixed the below issues, refresh this
page. Check the troubleshooting links at the bottom of this page if you need further assistance.
PHP
```
Your server's PHP satisfies all of Elgg's requirements.
```
Web server
```
We think your server is running the Apache web server. The rewrite test failed and the most likely cause is that AllowOverride is not set to All for Elgg's directory. This prevents Apache from processing the .htaccess file which contains the rewrite rules. A less likely cause is Apache is configured with an alias for your Elgg directory and you need to set the RewriteBase in your .htaccess. There are further instructions in the .htaccess file in your Elgg directory.
```
Database
```
The database requirements are checked when Elgg loads its database.
To correct this, replace the .htaccess file that Elgg created with one that you can edit:
```
cp -ip .htaccess temp-htaccess
rm .htaccess
mv temp-htaccess .htaccess
```
Edit the .htaccess file: Go to approximately line 101 (where it says #RewriteBase /) and add the line:
RewriteBase /~your-user-id/elgg/alpha/
Be sure to save the edited file.
Click the Refresh button.
If this hasn't fixed things, seek professional help.
Click the Next button.

Fill in the parameters appropriate to your MySQL installation.

Database installation

If you haven't already created a database for Elgg, do that now. Then fill in the values below to
initialize the Elgg database.

Database Username

elggalphauser

User that has full priviledges to the MySQL database that you created for Elgg

Database Password

secretpassword

Password for the above database user account

Database Name

elggalpha

Name of the Elgg database

Database Host

^‡

moxie:9999

Hostname of the MySQL server (usually localhost)
‡You might need to use 127.0.0.1:9999 for the host
    if you haven't set up MySQL as we've done.



Database Table Prefix

elgg_

The prefix given to all of Elgg's tables (usually elgg_)

Continue filling in forms as requested.

Configure site

Database has been installed.

We need some information about the site as we configure Elgg. If you haven't created a data directory for Elgg, you need to do so now.

Site Name

My Elgg Site version Alpha

The name of your new Elgg site

Site Email Address

your-user-id@oswego.edu

Email address used by Elgg for communication with users

Site URL

http://moxie.cs.oswego.edu/~your-user-id/elgg/alpha/

The address of the site (Elgg usually guesses this correctly)

Elgg Install Directory

/home/your-user-id/public_html/elgg/elgg.1.8.0.1/

The directory where you put the Elgg code (Elgg usually guesses this correctly)

Data Directory

/home/your-user-id/elgg/alpha/data

The directory that you created for Elgg to save files (the permissions on this directory are checked
when you click Next)

Default Site Access

Public

The default access level for new user created content

Create admin account

Site settings have been saved.

It is now time to create an administrator's account.

Display Name

The name that is displayed on the site for this account

Email Address

Username

Account username used for logging in

Password

Account password must be at least 6 characters long

Password Again

Retype password to confirm

dbCAN: a web server and DataBase for automated Carbohydrate-active enzyme ANnotation

Jit — Mon, 29 May 2017 05:39:29 -0500

dbCAN is a web server and DataBase for automated Carbohydrate-active enzyme ANnotation, funded by the BioEnergy Science Center of the DOE. Similar resources on the web include CAZy database and CAT. All data in dbCAN are generated based on the family classification from CAZy database while it has the following unique features compared with CAZy database and CAT:

dbCAN provides the capability of automated and comprehensive CAZyme annotation of a given genome submitted by the user;
dbCAN provides an explicitly defined signature domain for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced genomes;
dbCAN provides the most complete set of metagenomic CAZyme genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;
dbCAN provides a subfamily classification of the existing CAZyme families based on sequence similarities;
dbCAN make all pre-computed data freely available to the public, including sequence alignments, hidden markov models (HMMs) and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.

dbCAN is updated regularly when CAZy database created new families based on latest literature.

Address of the bookmark: http://csbl.bmb.uga.edu/dbCAN/index.php