BOL: Related items

Bioinformatics in Thailand !

Shruti Paniwala — Wed, 28 Apr 2021 02:04:56 -0500

Our international PhD and master programs are designed for students who desire focused training in the elements of biology, computer science, and information technology needed for a successful career in the exciting new discipline of Bioinformatics & Systems Biology. Students in our program will receive comprehensive training in omics analysis, database design and management, software engineering and programming (including web-based development), simulation techniques and modeling, and data integration. Each student will apply their skills to a practical project, where they will design and implement a solution to a real-world problem under the guidance of an experienced mentor in industry or academia.

https://bioinformatics.kmutt.ac.th/about.html

Duangrudee Tanramluk (Ajarn Wi) uses computational biology and machine learning to tackle the key to drug design problems via MANORAA webserver.

https://mb.mahidol.ac.th/en/bioinformatics/

https://graduate.mahidol.ac.th/inter/

This international Doctorate programme is designed to further broaden students’ knowledge in Bioinformatics and Molecular Biology to their maximum capability.

http://www.mbb.psu.ac.th/programmes/phd

Ph.D. program in Bioinformatics and Computational Biology is a joint effort of the Faculty of Science and Faculty of Medicine, Chulalongkorn University. The program has study plans for both applicants who hold a bachelor’s degree and applicants who hold a master’s degree in any related fields of study.

http://www.bioinfo.sc.chula.ac.th/ph-d-program-specialization/

Additional detail

https://www.biotec.or.th/en/index.php/research/research-units/genome-technology-research-unit

https://tbrcnetwork.org/labtbrc/index.php/bioinformatics-and-chemoinformatics/

https://genomicsthailand.com/Genomic/home

Address of the bookmark: https://bioinformatics.kmutt.ac.th/

Virus 3D Animation

Sat, 26 Oct 2013 09:01:27 -0500

piranha.dl facebook site: http://www.facebook.com/home.php?#!/pages/piranhadl-3D/131721586891915

Mosquito species known for transmitting the Dengue virus

BioStar — Wed, 03 Apr 2024 00:05:51 -0500

Here is a list of mosquito species known for transmitting the Dengue virus along with essential and applied information about each species:

1. Aedes aegypti:
- Geographical Distribution: Found in tropical and subtropical regions worldwide.
- Biting Behavior: Daytime biter, prefers feeding indoors, often around human dwellings.
- Role in Dengue Transmission: Primary vector responsible for transmitting Dengue virus to humans.

2. Aedes albopictus (Asian tiger mosquito):
- Geographical Distribution: Found in tropical, subtropical, and temperate regions worldwide.
- Biting Behavior: Daytime biter, feeds both indoors and outdoors, aggressive feeder.
- Role in Dengue Transmission: Secondary vector, can transmit Dengue virus to humans.

3. Aedes polynesiensis:
- Geographical Distribution: Found in Pacific Islands and coastal regions.
- Biting Behavior: Daytime biter, prefers feeding outdoors, often near coastal areas.
- Role in Dengue Transmission: Vector of Dengue virus in specific geographic regions.

4. Aedes scutellaris:
- Geographical Distribution: Found in Southeast Asia, Pacific Islands, and coastal regions.
- Biting Behavior: Daytime feeder, active in shaded areas, prefers outdoor environments.
- Role in Dengue Transmission: Vector of Dengue virus, particularly in coastal areas.

5. Aedes africanus:
- Geographical Distribution: Found in parts of Africa, including forested areas.
- Biting Behavior: Daytime feeder, prefers shaded areas, bites humans and other animals.
- Role in Dengue Transmission: Vector of Dengue virus in African regions.

Understanding the geographical distribution and biting behavior of these mosquito species is crucial for implementing effective control and prevention strategies to reduce Dengue virus transmission.

Influenza animation - flu virus mechanism

Thu, 17 Oct 2013 19:43:13 -0500

Animation of the mechanism of an influenza virus and how Crucell's antibodies target the HA1 proteins on the virus and prevent further spread of influenza. Client: Crucell Direction, Design & Animation: Daniel Lim, 2Preform Music & Sound Design: Javier Barrero, Logical Disorder Production Company: David Hager, All Terrain Media

Comparison of Short Read De Novo Alignment Algorithms

Rahul Agarwal — Wed, 21 Aug 2013 07:56:01 -0500

Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.

Title: Comparison of Short Read De Novo Alignment Algorithms

Author: Nikhil Gopal

Address of the bookmark: http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf

PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach

Rahul Nayak — Tue, 05 Jun 2018 09:57:11 -0500

PERGA - Paired End Reads Guided Assembler PERGA is a novel sequence reads guided de novo assembly approach which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds. Instead of using single-end reads to construct contig, PERGA uses paired-end reads and different read overlap sizes from O ≥ Omax to Omin to resolve the gaps and branches. Moreover, by constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. PERGA will try to extend the contigs by all feasible nucleotides and determine if these multiple extensions due to sequencing errors or repeats by using looking ahead technology, and it also try to separate the different repeats of nearby genomic regions to make the assembly result more longer and accurate. The simulated E.coli paired-end reads data are generated using GemSim (KE McElroy, F Luciani, T Thomas. Gemsim: General, Error-Model Based Simulator of Next-Generation Sequencing Data. BMC Genomics 2012, 13:74), with coverage 50x, 60x, 100x, read lengths 100-bp, and can be downloaded from https://github.com/zhuxiao/data_PERGA.

Address of the bookmark: https://github.com/hitbio/PERGA

ASplice: a scalable and memory-efficient algorithm for de novo transcriptome assembly

Rahul Nayak — Tue, 03 Jul 2018 04:09:46 -0500

With increased availability of de novo assembly algorithms, it is feasible to study entire transcriptomes of non-model organisms. While algorithms are available that are specifically designed for performing transcriptome assembly from high-throughput sequencing data, they are very memory-intensive, limiting their applications to small data sets with few libraries. Texas A&M University researchers develop a transcriptome assembly algorithm that recovers alternatively spliced isoforms and expression levels while utilizing as many RNA-Seq libraries as possible that contain hundreds of gigabases of data. New techniques are developed so that computations can be performed on a computing cluster with moderate amount of physical memory. Availability – A software program that implements the algorithm is available at: http://faculty.cse.tamu.edu/shsze/asplice. Sze SH, Pimsler ML, Tomberlin JK, Jones CD, Tarone AM. (2017) A scalable and memory-efficient algorithm for de novo transcriptome assembly of non-model organisms. BMC Genomics 18(Suppl 4):387.

Address of the bookmark: http://faculty.cse.tamu.edu/shsze/asplice/

MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph

Jit — Wed, 14 Nov 2018 04:50:27 -0600

MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct de Bruijn graph (SdBG) to achieve low memory assembly. MEGAHIT can optionally utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.

https://academic.oup.com/bioinformatics/article/31/10/1674/177884

Address of the bookmark: https://github.com/voutcn/megahit

NxRepair: error correction in de novo assemblies using Nextera Mate Pair Reads

BioStar — Thu, 24 Jan 2019 10:35:12 -0600

NxRepair is a python module that automatically detects large structural errors in de novo assemblies using Nextera mate pair reads. The decector will break a contig at the site of an identified misassembly and will generate a new fasta file containing both the corrected contigs and the correct, unaffected contigs.

https://nxrepair.readthedocs.io/en/latest/tutorial.html

nxrepair aligned_matepairs.bam assemblyfasta.fasta error_locations.csv new_fasta.fasta

Address of the bookmark: https://github.com/rebeccaroisin/nxrepair

SDA: Long-read sequence and assembly of segmental duplications

Jit — Tue, 05 Mar 2019 10:00:57 -0600

Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs.

https://github.com/mvollger/SDA

Address of the bookmark: https://www.nature.com/articles/s41592-018-0236-3