Laboratory for Bioinformatics and Computational Biology

A PhD position will soon be open in the LBCB. The project lasts for four years and will be concerned with detection of microbes present in a sequenced sample. Such problems are solved by various graph algorithms and using artificial intelligence and machine learning methods. Potential candidates (last year student or master degree in computing, physics or mathematics) need to be familiar with C/C++ programming language and have basic knowedge of algorithms. Experience with artificial intelligence and machine learging is considered an advantage. Research results will be applicable in genetics, medicine, biotechnology and other areas.

Interested parties can contact head of the Laboratory, prof Mile Šikić.

Racon version 1.0 was recently pushed to github. It is faster, consumes less memory and has support for FASTA format and Illumina reads for both error correction and consensus/polishing. Read about it here: http://complex.zesoi.fer.hr/index.php/en/blog-en/58-racon-1-0-release.

Racon 1.0.0 release

We have tested the ability of Minimap2 to map RNA-seq reads on our test datasets. The results are described in the first blog on the official LBCB pages:

GMAP Vs Minimap2 Web pages for Laboratory for Bioinformatics and Computational biology at the Faculty of Electrical Engineering and Computing, University of Zagreb

Our paper "Evaluation of tools for long read RNA-seq splice-aware alignment" has been accepted for publication by Oxford Journals Bioinformatics.
The paper explores how existing RNA aligners cope with 3rd generation sequencing reads. Several RNA aligners were tested on synthetic and real data. Error correction prior to alignment is shown to improve the results.
Link: https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx668/4562330/Evaluation-of-tools-for-long-read-RNAseq.

Evaluation of tools for long read RNA-seq splice-aware alignment | Bioinformatics | Oxford Academic

Our new paper, Fast and simple algorithm for computing both LCSk and LCSk+, is available in preprint on bioRxiv (https://arxiv.org/pdf/1705.07279.pdf). The main drawback of the current state-of-the-art algorithms for computing LCSk ad LCSk+ is that they are geared either towards average case or towards the worst case scenario. Our paper presents a single algorithm that can be used to compute both LCSk and LCSk+ which outperforms currently available algorithms and requires only basic data structures simplifying its application. The paper also describes the algorithm that can be used to reconstruct the solution which offers significant improvement in terms of memory consumption.

Our paper Evaulation of tools for long read RNA-seq splice-aware alignment in preprint on bioRxiv. The paper explores how existing RNA aligners cope with 3rd generation sequencing reads. Five RNA aligners were tested on synthetic and real data. Error correction prior to alignment is shown to improve the results.

link: http://biorxiv.org/content/early/2017/04/11/126656

https://www.wired.com/2017/03/biologists-teaching-code-survive

Want to Make It as a Biologist? Better Learn to Code Their schools may not have caught up yet, but these biologists are embracing the era of big data.

Edlib paper accepted for publication in Bioinformatics!
Edlib is a C/C++ library for fast and exact sequence alignment using edit distance. Is is easy to use, flexible and low on memory usage. We expect it to be easily adopted as a building block for future bioinformatics tools.
The paper has recently been accepted for publication in Bioinformatics (https://doi.org/10.1093/bioinformatics/btw753).

The paper is based on the master thesis by Martin Šošić

Comparison of Miniasm+Racon with other pipelines

Racon paper accepted for publication!

Our paper with the title Fast and accurate de novo genome assembly from long uncorrected reads has been accepted for publication by Genome Research (http://genome.cshlp.org/content/early/2017/01/18/gr.214270.116).

The authors of the paper are Robert Vaser mag.comp. and prof. Mile Šikić from Faculty of Electrical Engineering and Computing, Dr. Ivan Sović from Ruđer Bošković Institute and Dr. Niranjan Nagarajan from A*STAR Genome Institute of Singapore.

We are happy to announce that on October 4th 2016 Ivan Sović has successfully completed and defended his PhD thesis with the title: Algorithms for de novo genome assembly from third generation sequencing data

New paper on efficient protein database search published by Oxford Journals Bioinformatics!

Our new paper: SWORD - a higly efficient protein database search has been accepted at ECCB 2016. Full paper is available at:
(http://bioinformatics.oxfordjournals.org/content/32/17/i680.full)