BOL: Related items

Professor/Associate Professor/ Assistant Professor at Chettinad Academy of Research and Education

Sat, 24 May 2014 00:00:15 -0500

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

minialign: fast and accurate alignment tool for PacBio and Nanopore long reads

Jit — Thu, 24 May 2018 08:33:26 -0500

Minialign is a little bit fast and moderately accurate nucleotide sequence alignment tool designed for PacBio and Nanopore long reads. It is built on three key algorithms, minimizer-based index of the minimap overlapper, array-based seed chaining, and SIMD-parallel Smith-Waterman-Gotoh extension.

Address of the bookmark: https://github.com/ocxtal/minialign

The Minerva Research Group for Bioinformatics

Tue, 27 May 2014 15:48:14 -0500

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

LoRMA: A tool for correcting sequencing errors in long reads

Abhimanyu Singh — Thu, 06 Sep 2018 16:21:01 -0500

An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of k-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75×, the throughput of the new method is at least 20% higher.

conda install -c atgc-montpellier lorma

Address of the bookmark: https://gite.lirmm.fr/lorma/lorma-releases/wikis/home

Monitor running jobs on Linux server

Jitendra Narayan — Fri, 06 Jun 2014 16:18:43 -0500

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:

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...

FLAS: fast and high throughput algorithm for PacBio long read self-correction.

Jit — Sat, 22 Jun 2019 12:16:39 -0500

FLAS, a wrapper algorithm of MECAT, to achieve high throughput long read self-correction while keeping MECAT's fast speed. FLAS finds additional alignments from MECAT prealigned long reads to improve the correction throughput, and removes misalignments for accuracy.

Address of the bookmark: https://github.com/baoe/flas

Genomics and Personalized Medicine Breakthroughs

Sun, 01 Jun 2014 23:40:14 -0500

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.

LoReTTA, a user-friendly tool for assembling viral genomes from PacBio sequence data

Neel — Wed, 23 Jun 2021 07:54:53 -0500

LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing de novo assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads.

https://academic.oup.com/ve/article/7/1/veab042/6248116

Address of the bookmark: https://academic.oup.com/ve/article/7/1/veab042/6248116

Assistant Professor in Bioinformatics at Dr. D. Y. Patil Biotechnology & Bioinformatics Institute

Tue, 03 Jun 2014 19:54:15 -0500

Dr. D. Y. Patil Biotechnology & Bioinformatics Institute
Tathawade, Pune 411033.

Assistant Professor in Bioinformatics

Essential :
First Class Master’s Degree in the appropriate branch of Life Sciences / Technology (Tech.)
OR
Ph.D in Life Sciences or in the respective subject area of specialization
OR
Good Academic record with at least 55% marks (or an equivalent grade) at the Master’s Degree level, in the relevant subject or an equivalent degree from an Indian / Foreign University.
Besides fulfilling the above qualifications, candidates should have cleared the eligibility test (NET) for lecturers conducted by the UGC, CSIR or similar test accredited by the UGC and as per the requirements of UGC guidelines.

Desirable :
Teaching, research industrial and/or professional experience in a reputed organization.
Papers presented at Conferences and/or in refereed journals

Note : Application are invited in prescribed form Click here for Application Form
Kindly send your applications to “Registrar, Dr. D. Y. Patil Vidyapeeth, Pune, Sant Tukaram Nagar, Pimpri, Pune – 411018., Maharashtra, India.” should reach in the University office within 15 days from the publication.

More Info: http://www.dpu.edu.in/BiotechResearchPositions.aspx

CoLoRMap: Correcting Long Reads by Mapping short reads

Jit — Mon, 20 Aug 2018 14:17:05 -0500

Second generation sequencing technologies paved the way to an exceptional increase in the number of sequenced genomes, both prokaryotic and eukaryotic. However, short reads are difficult to assemble and often lead to highly fragmented assemblies. The recent developments in long reads sequencing methods offer a promising way to address this issue. However, so far long reads are characterized by a high error rate, and assembling from long reads require a high depth of coverage. This motivates the development of hybrid approaches that leverage the high quality of short reads to correct errors in long reads.We introduce CoLoRMap, a hybrid method for correcting noisy long reads, such as the ones produced by PacBio sequencing technology, using high-quality Illumina paired-end reads mapped onto the long reads. Our algorithm is based on two novel ideas: using a classical shortest path algorithm to find a sequence of overlapping short reads that minimizes the edit score to a long read and extending corrected regions by local assembly of unmapped mates of mapped short reads. Our results on bacterial, fungal and insect data sets show that CoLoRMap compares well with existing hybrid correction methods.The source code of CoLoRMap is freely available for non-commercial use at https://github.com/sfu-compbio/colormap

ehaghshe@sfu.ca or cedric.chauve@sfu.ca

Address of the bookmark: https://github.com/sfu-compbio/colormap