<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/42499?offset=90 https://bioinformaticsonline.com/bookmarks/view/43040/coronavir-computational-resources-on-novel-coronavirus-sars-cov-2-or-covid-19 Tue, 27 Apr 2021 01:58:36 -0500 https://bioinformaticsonline.com/bookmarks/view/43040/coronavir-computational-resources-on-novel-coronavirus-sars-cov-2-or-covid-19 <![CDATA[CoronaVIR: Computational Resources on Novel Coronavirus (SARS-CoV-2 or COVID-19)]]>

Aim of this web site is to facilitate the scientific community to fight against severe pandemic disease COVID-19 caused by SARS-CoV-2. Here, We have collected and organized information related to novel strain of coronavirus, i.e. SARS-CoV-2.and its resulting disease COVID-19 from the literature and other resources from the Internet. We are providing links to appropriate literature. Moreover, we are Bioinformatics Group, based on our knowledge and expertise, we are also proposing potential diagnostics primers, peptide and RNA based vaccine candidates and potential drug molecules. These are predicted candidates, need to be validated by experimental Researchers, who have appropriate infrastructure. It is an integrated multi-omics repository dedicated to current genomic, proteomic, diagnostic and therapeutic knowledge about coronaviruses particularly the recent strain, i.e. SARS-CoV-2 or 2019-nCoV. This web resource will be helpful for the researchers engaged in the development of therapies and drugs for the COVID-19. The information is collected from various available resources.
Cite: Patiyal, Sumeet, et al. “A Web-based Platform on COVID-19 to Maintain Predicted Diagnostic, Drug
and Vaccine Candidates.” Monoclon Antib Immunodiagn Immunother. doi.org/10.1089/mab.2020.0035

 

Address of the bookmark: https://webs.iiitd.edu.in/raghava/coronavir/

]]> LEGE https://bioinformaticsonline.com/researchlabs/view/10739/science-for-life-laboratory-scilifelab-sweden Sat, 10 May 2014 06:22:30 -0500 <![CDATA[Science for Life Laboratory (SciLifeLab)-Sweden]]> Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.

Webpage : https://www.scilifelab.se/about-us/
Opportunity: https://www.scilifelab.se/about-us/career/

]]> https://bioinformaticsonline.com/blog/view/41804/useful-links-to-therapy-disease-drug-and-drug-target-network-data Mon, 01 Jun 2020 11:47:51 -0500 https://bioinformaticsonline.com/blog/view/41804/useful-links-to-therapy-disease-drug-and-drug-target-network-data <![CDATA[Useful links to therapy, disease, drug and drug-target network data:]]> Useful links to therapy, disease, drug and drug-target network data:

DrugBank:

a bioinformatics- cheminformatics resource combining detailed drug data with comprehensive drug target information with >4900 drug (~3500 experimental) and >1500 non-redundant protein entries http://www.drugbank.ca/

Drug-Target Network:

network data of 890 drugs and 394 target human proteins http://www.nature.com/nbt/journal/v25/ n10/suppinfo/nbt1338_S1.html

Drug-Therapy Network:

three layers of drug-therapy networks according to the ATC classification http://www.biomedcentral.com/1471-2210/8/5/additional/

FDA Orange Book:

approved drug products with therapeutic equivalence evaluations http://www.fda.gov/cder/ob/HIDdb: Thomson Investigational drugs database including information on 107000 patents, 25000 investigational drugs and 80000 chemical structures http://scientific.thomson.com/products/iddb/HOMIM: a knowledgebase of human genes and genetic disorders http://www.ncbi.nlm.nih.gov/ sites/entrez?db=omim

PDTD:

3D drug target structure database with a target identification option http://www.dddc.ac.cn/pdtd/

Predicted drug targets:

a set of 1383 predicted drug targets http://www.biomedcentral.com/1471-2105/8/353/additional/ [25] Protein ligand network: a network of 4208 ligands and ~15000 binding sites http://pbil.kaist.ac.kr/~parkkw/Lnet/

TDR Targets Database:

identification and ranking targets against neglected tropical diseases http://tdrtargets.org/

Therapeutic Target Database:

lists >1500 therapeutic targets, disease conditions and corresponding drugs http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp

]]> Jit https://bioinformaticsonline.com/opportunity/view/10841/ra-at-iisr-kozhikode Thu, 15 May 2014 10:08:09 -0500 <![CDATA[RA at IISR Kozhikode]]> INDIAN INSTITUTE OF SPICES RESEARCH
(Indian Council of Agricultural Research)
Marikunnu P.O., Kozhikode – 673 012, Kerala

Walk- in- Test cum Interview (based on test) for the selection of Research Associate

under the scheme “Distributed Information Sub Centre –DISC” & Research Assistant under scheme “Phytophthora, Fusarium and Ralstonia diseases of Horticultural and Field Crops” will be held at this Institute as per details indicated below.

WALK -IN- TEST CUM INTERVIEW

Name of the post : Research Associate

Date of Interview : 21-05-2014 at 10.00 AM

No. of posts : One

Qualifications : a)Essential

Ph.D Degree in Bioinformatics OR : Masters degree in Bioinformatics with a minimum of
60% marks or equivalent OGPA with at least two years research experience as evidenced from fellowship/ associateship/training/published papers etc.

b)Desirable: Experience in NGS data analysis.

Emoluments : Rs. 23,000/- per month + HRA (Masters Degree Holders)

Rs. 24,000/- per month + HRA (Ph.D Degree Holders)

Upper age limit : 40 years for Men & 45 years for Women as on date of Interview (Upper Age limits are relaxable for SC, ST and OBC candidates as per Govt. of India norms (at present 5 years for SC/ST and 3 years for OBC)

Duration of Project : Till 31-03-2017.

Title of Assigment : Research Assistant (on contract basis)

No. of vacancy : One

Qualification : Essential : Post Graduation in Bioinformatics and Minimum one year experience in NGS data analysis

Desirable : Experience in Perl/Python/R

Remuneration : Rs. 20,000/- per month (consolidated)

Scope of work :

1. Analysis of different file formats and their conversions.

2. Assessing the quality of data and filtering of raw reads.
3. Assembling the raw reads-de novo as well as reference mapping.
4. Compression of aligned reads using Jam tools
5. RNA-seq. Analysis
6. Differential expression testing involving Normalization, Statistical testing, heat map generation & hierarchical clustering
7. Annotating the assembled genome and geneet testing and their validation
8. Metabolic pathway analysis
9. Comparative genomics
10. Setting up of genome browsers.

Period of Assigment : Initially for six months.

Date & Venue of Interview : 21-05-2014 at IISR, Kozhikode at 10.00 AM

More at http://www.spices.res.in/pdf/disc-advtmnt.pdf

]]> https://bioinformaticsonline.com/pages/view/1130/bioinformatics-courses-around-the-world Fri, 19 Jul 2013 02:43:46 -0500 https://bioinformaticsonline.com/pages/view/1130/bioinformatics-courses-around-the-world <![CDATA[Bioinformatics Courses Around the World]]> Bioinformatics Courses around the world


Here is the list Bioinformatics courses offered around the world. Reasons for constructing this page are:

  1. To show the extent of growth of this new discipline
  2. To provide a resource for students, and academics and
  3. To access notes on the subject to allow some brief comparisons between courses.

The graduate courses outlined in the table mainly exist as a coursework component of an MSc or PhD degree. Of course, many institutions will also have pure research programs in Bioinformatics at the Hons, MSc, or PhD level and will not have a 'coursework component'. These research programs may not always reflect the main research program of the institution since the research depends upon the interests of a particular individual or small team within that institution. It is difficult to track these individual research programs. Consequently, we have not included all institutions with a bioinformatics research project. Bioinformatics is an interdisciplinary subject and this is reflected in the fact that the courses are offered by departments or schools as diverse as: computer science, biochemistry, molecular biology, microbiology, engineering, and mathematics. Similarly, bioinformatics may also be known by other names such as: computational biology, biocomputing, molecular informatics, computational molecular biology, biological information theory, molecular phylogenetics, and molecular bioinformatics.

Bioinformatics University Courses

US

Canada

Europe

UK

Sweden

Norway

Germany

Finland

France

Denmark

Belgium

Switzerland

Austria

Israel

New Zealand

Australia

Asia & South Pacific

Africa


Others:


Advanced Courses and Papers

 

If your university is not there in the list, please let me know info_at_bioinformaticsonline.com

]]> Jitendra Narayan https://bioinformaticsonline.com/opportunity/view/11000/professorassociate-professor-assistant-professor-at-chettinad-academy-of-research-and-education Sat, 24 May 2014 00:00:15 -0500 <![CDATA[Professor/Associate Professor/ Assistant Professor at Chettinad Academy of Research and Education]]> OPEN FACULTY POSITION

Chettinad Academy of Research and Education (CARE) invites applications from eligible and translational research-oriented candidates to the posts of Professor/Associate Professor/ Assistant Professor Computational Biology, Bioinformatics, and Pharmaceutical Chemistry.

Emoluments: As per UGC norms (Adequate Compensation for Postdoctoral/Teaching experience)

Candidates fulfilling the eligibility criteria as per the UGC norms can send their full CV with copies of certificates and reference letters to the following address by post or by e-mail on or before 31st May 2014

The Registrar,
Chettinad Academy of Research and Education,
Chettinad Health City
Kelambakkam, Chennai 603 103
Tamil Nadu
T +91 (0)44 4741 1000
F +91 (0)44 4741 1011
Email: jobs @chettinadhealthcity.com

Advertisement: http://182.73.176.163/chc/ads2014.pdf

]]> https://bioinformaticsonline.com/blog/view/22454/one-page-r-survival-guide Thu, 28 May 2015 21:10:12 -0500 https://bioinformaticsonline.com/blog/view/22454/one-page-r-survival-guide <![CDATA[One page R survival guide !!]]> There any many of the documents have been developed and tested by scientist around the world. I found this one really useful. The data used is available for download as data.zip.

Reference@http://www.datasciencecentral.com/profiles/blogs/one-page-r-a-survival-guide-to-data-science-with-r

  • Templates for the Data Scientist
    1. A Template for Preparing Data: *OnePageR - *R
    2. A Template for Building Models: *OnePageR - *R
  • Getting Started as a Data Scientist
    1. Getting Started with R and Rattle: *Lecture - *Laboratory
    2. Introducing and Interacting with R: *Lecture - *Laboratory
    3. BasicR - OnePage(R) - Writing R scripts
  • Dealing With Data
    1. Read Data into R: *OnePageR - *R
    2. Explore and Summarise Data: *OnePageR - *R
    3. Transform Data: *OnePageR - *R
    4. Dealing with Dates and Time: (PDF, R) Dates and Time
    5. Visualising Data with GGPlot2: *OnePageR - *R
    6. Visualising Data with Maps *OnePageR - *R
    7. Spatial (R) Spatial Analysis
    8. Handling Big Data *OnePageR - *R
  • Descriptive Analytics
    1. Cluster Analysis: *Lecture - *OnePageR - *R
    2. Association Analysis: *Lecture
  • Predictive Analytics
    1. Decision Trees: *Lecture - *OnePageR - *R - *Rattle
    2. Ensembles of Decision Trees: *Lecture - *OnePageR - *R
    3. SVM (R)
    4. KernLab (R)
    5. NeuralNetworks (R)
    6. NNet (R)
  • Model Delivery
    1. Evaluating Models: *OnePageR - *R
    2. Evaluation (R)
    3. Scoring (R)
    4. PMML (R) Exporting Models for Deployment
  • Advanced Topics
    1. Text Mining: *OnePageR - *R
  • Advanced R Topics
    1. Plots (PDF, R) Miscellaneous Plots
    2. Functions (PDF, R) Writing Functions in R
    3. Parallel (PDF, R) Parallel Execution
    4. Packaging (R) Pulling it Together into a Package
    5. Doing R with Style: *OnePageR - *R
    6. Literate Data Mining with KnitR: *Lecture - *OnePageR - *
]]> Rahul Nayak https://bioinformaticsonline.com/researchlabs/view/11107/the-minerva-research-group-for-bioinformatics Tue, 27 May 2014 15:48:14 -0500 <![CDATA[The Minerva Research Group for Bioinformatics]]> The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.

http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27

Kelso Group
Department of Evolutionary Genetics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
Germany
Phone: +49 341 3550 500

Job:
http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40

]]> https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server Fri, 06 Jun 2014 16:18:43 -0500 https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server <![CDATA[Monitor running jobs on Linux server]]> You as a bioinformatican run lots of program on your servers. Sometime the shared server is also used by your colleague. If server is busy you sometime need to check the running programs and want to monitor the running programs as well. The "top" command will come in handy when you need to find out if things are still running, how long they’ve been running, or how much memory is being used.

‘top’ is very simple to run: type

%% top

You’ll get a screen that looks like this, and is updated regularly:

image
Simple, right? Heh.

First! Note that you can use ‘q’ or ‘CTRL-C’ to exit from ‘top’.

Now let’s read and understand at each line independently.

The first line:

top - 23:00:48 up 39 days,  2 user,  load average: 0.00, 0.00, 0.00

The first line tells you the current time, how long the machine has been up, how many users are logged in, and the short/medium/long-term compute load on the machine. If you run something for a long time, you’ll see these numbers go up. Right now, the machine is basically just sitting there, so these are all close to 0.

The second line:

Tasks:  239 total,   1 running,  238 sleeping,   0 stopped,   0 zombie

This line tells you how many processes are running. If you are using laptops machines it’s not so interesting because you really are the only one using this machine.

Cpu(s):  0.0%us,  0.0%sy,  0.0%ni,100.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st

This line contains the CPU load. The first two numbers are how busy the system is doing computation (“us” stands for “user”) and how busy the system is doing system-y things like accessing disks or network (“sy” stands for “system”). We’ll talk more about this later.

Mem:   49457320k total,    3492174k used,  14535596k free,    1435148k buffers

This should be easy to understand – how much memory you’re using!

Swap:   539356k total,   28332k used,   836562k free,    29862014k cached

Swap is just on-disk memory that can be used to “swap” out programs from main memory. Again, we’ll talk about this later.:

PID USER      PR  NI  VIRT  RES  SHR S %CPU %MEM    TIME+  COMMAND
  1 root      39   19  0  0  0 S  0.0  0.0   246:57.22 kipmi0
  2 root      RT   0     0    0    0 S  0.0  0.0   0:00.00 migration/0

And... finally! What’s actually running! The two most important numbers are the %CPU and %MEM towards the right, as well as the COMMAND. This tells you how compute- and memory-intensive your program is. Right now, nothing’s running so the numbers aren’t very interesting, but just wait until we run something...

]]> Jitendra Narayan https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs Sun, 01 Jun 2014 23:40:14 -0500 https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs <![CDATA[Genomics and Personalized Medicine Breakthroughs]]> http://bit.ly/e8QGzY Human genome mapping is now enabling a breakthrough in medical innovation -- personalized medicine. What does this mean for patients? We can now identify predispositions to disease, predict how we metabolize drugs, and figure out what kinds of treatments we may respond to, and even determine when a drug may give us an adverse reaction. All medical specialties benefit from human genome intelligence -- oncology saw the first impacts -- but advances are now being seen in cardiology, obstetrics and gynecology, pediatric diseases, gastroenterology, rheumatology, immunology and other areas. This video covers the areas that genetic medicine is impacting and where the future of genomic medicine is heading.]]>