BOL: Related items

GenomeTools: The versatile open source genome analysis software

Jit — Wed, 07 Feb 2018 10:44:18 -0600

The GenomeTools genome analysis system is a free collection of bioinformatics tools (in the realm of genome informatics) combined into a single binary named gt. It is based on a C library named “libgenometools” which consists of several modules.

If you are interested in gene prediction, have a look at GenomeThreader.

Address of the bookmark: http://genometools.org/

Troyanskaya Lab

Tue, 04 Feb 2020 06:40:36 -0600

The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.

https://function.princeton.edu/

SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis

BioStar — Mon, 17 Aug 2020 05:21:09 -0500

SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, …).
The bioinformatics treatment is based on Vsearch [Rognes 2016] which showed to be both accurate and fast [Wescott 2015].The statistical analysis is based on DESeq2 R package [Anders and Huber 2010] which robustly identifies the differential abundant features as suggested in [McMurdie and Holmes 2014] and [Jonsson2016]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [Love 2014].
SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available here and a poster here.

More at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4

Address of the bookmark: https://github.com/aghozlane/shaman

Useful Bioinformatics Analysis Tools !

Neel — Thu, 23 Dec 2021 23:10:02 -0600

CoMeta

Classificier of reads from metagenomic sequencing experiments.

• Kawulok, J., Deorowicz, S., CoMeta: Classification of Metagenomes Using k-mers, PLOS ONE, 2015; 10(4):1–23,

CoMSA

Compressor of multiple sequence alignments of proteins.

• Deorowicz, S., Walczyszyn, J., Debudaj-Grabysz, A., CoMSA: compression of protein multiple sequence alignment files, Bioinformatics, 2019; 35(2):22–234,

DSRC

Compressor of sequencing reads.

• Roguski, L., Deorowicz, S., DSRC 2: Industry-oriented compression of FASTQ files, Bioinformatics, 2014; 30(15):2213–2215,
• Deorowicz, S., Grabowski, Sz., Compression of DNA sequences in FASTQ format, Bioinformatics, 2011; 27(6):860–862,

FAMSA

Multiple sequence alignment designed for huge families of proteins (even containing hundreds of thousands of sequences).

• Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., FAMSA: Fast and accurate multiple sequence alignment of huge protein families, Scientific Reports, 2016; 6(33964):

FaStore

Compressor of FASTQ files.

• Roguski, L., Ochoa, I., Hernaez, M., Deorowicz, S., FaStore - a space-saving solution for raw sequencing data, Bioinformatics, 2018; 34(16):2748–2756,

FQSqueezer

Experimental high-end compressor of FASTQ files.

• Deorowicz, S., FQSqueezer: k-mer-based compression of sequencing data, Scientific Reports, 2020; 10(578):

GDC

Compressor of collections of genome sequences.

• Deorowicz, S., Danek, A., Niemiec, M., GDC 2: Compression of large collections of genomes, Scientific Reports, 2015; 5(11565):1–12,
• Deorowicz, S., Grabowski, Sz., Robust relative compression of genomes with random access, Bioinformatics, 2011; 27(21):2979–2986,

GTC

Genotype databases compressor with support for fast queries.

• Danek, A., Deorowicz, S., GTC: how to maintain huge genotype collections in a compressed form, Bioinformatics, 2018; 34(11):1834–1840,

GTShark

Genotypes compressor.

• Deorowicz, S., Danek, A., GTShark: Genotype compression in large projects, Bioinformatics, 2019; 35(22):4791–4793,

KMC

Memory frugal k-mer counter.

•  Kokot, M., Długosz, M., Deorowicz, S., KMC 3: counting and manipulating k -mer statistics, Bioinformatics, 2017; 33(17):2759–2761,
•  Deorowicz, S., Kokot, M., Grabowski, Sz., Debudaj-Grabysz, A., KMC 2: Fast and resource-frugal k-mer counting, Bioinformatics, 2015; 31(10):1569–1576,
•  Deorowicz, S., Debudaj-Grabysz, A., Grabowski, Sz., Disk-based k-mer counting on a PC, BMC Bioinformatics, 2013; 14():Article no. 160,

Kmer-db

Tool for estimation of evolutionary distances in a collection of genomes.

• Deorowicz, S., Gudys, A., Dlugosz, M., Kokot, M., Danek, A., Kmer-db: instant evolutionary distance estimation, Bioinformatics, 2019; 35(1):133–136,

MuGI

Index allowing queries for a collection of multiple genome sequences.

• Danek, A., Deorowicz, S., Grabowski, Sz., Indexes of Large Genome Collections on a PC, PLOS ONE, 2014; 9(10):e109384,

ORCOM

Experimental compressor of sequencing reads.

• Grabowski, Sz., Deorowicz, S., Roguski, L., Disk-based compression of data from genome sequencing, Bioinformatics, 2014; 31(9):1389–1395,

PgSA

Index allowing queries for a collection of sequencing reads.

• Kowalski, T., Grabowski, Sz., Deorowicz, S., Indexing arbitrary-length k-mers in sequencing reads, PLOS ONE, 2015; 10(7):1–16,

QuickProbs

Multiple sequence alignment designed especially for GPU.

• Gudys, A., Deorowicz, S., QuickProbs 2: towards rapid construction of high-quality alignments of large protein families, Scientific Reports, 2017; 7(41553):
• Gudys, A., Deorowicz, S., QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors, PLOS ONE, 2014; 9(2):e88901,

RECKONER

Read error corrector.

• Maciej Długosz, M., Deorowicz, S., RECKONER: read error corrector based on KMC, Bioinformatics, 2017; 33(7):1086–1089,

TGC

Compressor of collections of genomes given in Variant Call Format (VCF) files.

• Deorowicz, S., Danek, A., Grabowski, Sz., Genome compression: a novel approach for large collections, Bioinformatics, 2013; 29(20):2572–2578,

VCFShark

Compressor of VCF files.

• Deorowicz, S., Danek, A., GTShark: Genotype compression in large projects, biorxiv.org, 2020; ():

Whisper

Experimental mapper of whole genome sequencing data.

•  Deorowicz, S., Gudys, A., Whisper 2: indel-sensitive short read mapping, bioRxiv.org, 2019; :
•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz., Whisper: read sorting allows robust robust mapping of DNA sequencing data, Bioinformatics, 2019; 35(12):2043–2050,
•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz., Robust mapping of whole genome sequencing data, Poster at The Biology of Genomes Conference, 2017;

Structural polymorphism analysis from NGS data

Sat, 13 Jul 2013 17:12:47 -0500

The LabEx BASC (Biodiversity, Agroecosystems, Society, Climate), a network of 13 laboratories of the Paris-Saclay Scientific Cluster, is seeking a bioinformatician to analyze Next Generation Sequencing (NGS) data analysis. In the context of a flagship project aiming at understanding and improving the adaptive capacity of agroecosystems it will be critical to establish a link between sequence variation, functional variation, gene/protein expression and phenotypic adaptation.

The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).

The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development.

Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.

Bioinformatics Lecture Notes

LEGE — Tue, 01 Oct 2024 03:45:26 -0500

Study Resources for

ECM3413 - Bioinformatics

Contents

General Information

Lecture Slides

Past Exam Paper

Continuous Assessments

33rd Annual Convention of Indian Association for Cancer Research from 13th to 15th February 2014

Tue, 27 Aug 2013 10:37:08 -0500

RGCB is organizing the 33rd Annual Convention of Indian Association for Cancer Research from 13th to 15th February 2014 with the theme "Discovery, Innovation and Translation in Cancer Research"

Kindly log on to conference website http://rgcb.res.in/IACR2014 for further details and timely updates and registration. We shall truly appreciate if the same be circulated among your friends, scholars and students encouraging them to participate in the meet.

http://210.212.237.38/iacrconference/

3rd Annual Next Generation Sequencing Asia Congress 2013 at Singapore, Singapore

Wed, 14 Aug 2013 09:55:04 -0500

The 3rd Annual Next Generation Sequencing Asia Congress is to be held on the 22nd and 23rd of October 2013 in Singapore. Over the 2 days, the conference will provide an overview of the current options of next-generation sequencing platforms, technologies, applications and the newest computational tools for the analysis of next-generation sequencing data and analytical genomics as well as overcoming data management problems. The event will attract over 200 senior-level decision makers working in areas such as next generation sequencing, analytical genomics, computational biology, oncology, RNA profiling, molecular genomics, biomarkers, bioinformatics & data management and clinical & diagnostics development.

Dated : 22 Nov 2013 -23 Nov 2013

http://www.ngsasia-congress.com/

Clinical Genomics & Informatics Europe at Lisbon, Portugal

Wed, 14 Aug 2013 09:58:34 -0500

Bio-IT World and Cambridge Healthtech Institute's fifth international Clinical Genomics & Informatics Europe conference will feature four main tracks on Clinical Exome Sequencing, High Scale Computing, Genome Informatics, and RNA-Seq and Transcriptome Analysis, as well as two pre-conference symposia on Clinical Epigenetics and Quantitative Digital Detection Technologies. The conference will tackle the huge amounts of sequencing data produced by new technologies that have introduced significant challenges for bioinformatics, both in terms of the analysis and interpretation of data and clinical implementation of novel variants. Members of the international community will come together to look at the science and informatics required to utilize next generation sequencing for the molecular diagnosis of complex diseases.

Dated : 04 Dec 2013 - 06 Dec 2013

More at : http://www.clinicalgenomicsinformatics.com/

7th International Conference on Bioinformatics and Computational Biology (BICoB)

Rahul Agarwal — Mon, 06 Oct 2014 16:19:36 -0500

In recent years, computational biology and medical informatics have seen significant advances driven by computational techniques in bioinformatics making bioinformatics and computational biology among the most vibrant research areas. The 7th international conference on Bioinformatics and Computational Biology (BICoB-2015) provides an excellent venue for researchers and practitioners in the fields of bioinformatics and computational biology to present and publish their research results and techniques. The BICoB conference seeks original and high quality papers in the fields of bioinformatics, computational biology, systems biology, medical informatics and the related disciplines. We also encourage work in progress and research results in the emerging and evolutionary computational areas. Computational techniques have already enabled unprecedented advances in modern biology and medicine. Work in the computational methods related to, or with application in, bioinformatics is also encouraged including: data mining, text mining, machine learning, modeling and simulation, pattern recognition, data visualization, biostatistics, .etc. The topics of interest include (and are not limited to):
Genome analysis: Genome assembly, genome annotation, gene finding, alternative splicing, EST analysis and comparative genomics.
Sequence analysis: Multiple sequence alignment, sequence search and clustering, function prediction, motif discovery, functional site recognition in protein, RNA and DNA sequences.
Phylogenetics: Phylogeny estimation, models of evolution, comparative biological methods, population genetics.
Structural Bioinformatics: Structure matching, prediction, analysis and comparison; methods and tools for docking; protein design
Analysis of high-throughput biological data: Microarrays (nucleic acid, protein, array CGH, genome tiling, and other arrays), EST, SAGE, MPSS, proteomics, mass spectrometry.
Genetics and population analysis: Linkage analysis, association analysis, population simulation, haplotyping, marker discovery, genotype calling.
Systems biology: Systems approaches to molecular biology, multiscale modeling, pathways,gene networks.
Computational Proteomics: Filtering and indexing sequence databases, Peptide quantification and identification, Genome annotations via mass spectrometry, Identification of post-translational modifications, Structural genomics via mass spectrometry, Protein-protein interactions, Computational approaches to analysis of large scale Mass spectrometry data, Exploration and visualization of proteomic data, Data models and integration for proteomics and genomics, Querying and retrieval of proteomics and genomics data etc.

Authors of selected high quality papers in BICoB-2015 will be invited to submit extended version of their papers for possible publication in bioinformatics journals (Journal of Bioinformatics and Computational Biology JBCB).

Deadlines:

Paper Submission Deadline October 24, 2014
Notification of Acceptance December 15, 2014
Camera-Ready Manuscript January 16, 2015

Address of the bookmark: http://www.cs.umb.edu/bicob/

	This module runs in Semester 2.
	It is taught by Dr Ed Keedwell (Module Coordinator)
	Module Descriptor: ECM3413
	Lecture Times: Tuesday 5pm, 171\| Thursday, 171
	Workshop Times: Wednesday 11am Blue Room (Weeks 29,33 &40)
	Assessment: 2 CAs each worth 15% \| 1 Examination worth 70%

	PPT\|PDF\| Lecture 1 - Introduction to Bioinformatics (& Biology)
	PPT\|PDF\| Lecture 2 - Genome Sequences: from fragments to sequences
	PPT\|PDF\| Lecture 3 - Sequence Alignment 1
	PPT\|PDF\| Lecture 4 - Global Pairwise Sequence Alignment
	PPT\|PDF\| Lecture 5 - Local Pairwise Sequence Alignment (Smith-Waterman & BLAST)
	DOC\| Workshop 1 - Using BLAST and other Bioinformatics Databases
	PPT\|PDF\| Lecture 6 - Multiple Sequence Alignment
	PPT\|PDF\| Lecture 7 - BLAST (in more detail) & FASTA
	PPT\|PDF\| Lecture 8 - Sequence Alignment Conclusion & Other Sequence Analyses
	PPT\|PDF\| Lecture 9 - Markov Chains and Intro to Hidden Markov Models
	PPT\|PDF\| Lecture 10 - Hidden Markov Models
	PPT\|PDF\| Lecture 11 - Classification in Bioinformatics
	DOC\|Workshop 2 - Using See5
	Workshop Data - Part 1 - adult.names \| adult.data \| adult.test, Part 3 - wdbc.names\| wdbc.data
	PPT\|PDF\| Lecture 12 - Gene Expression Data
	PPT\|PDF\| Lecture 13 - Decision Trees and Gene Expression Classification
	PPT\|PDF\| Lecture 14 - Other Methods for Gene Expression Classification
	PPT\|PDF\| Lecture 15 - Gene Regulation
	PPT\|PDF\| Lecture 16 - Neural Networks in Gene Expression Analysis
	PPT\|PDF\| Lecture 17 - Genome Analysis
	PPT\|PDF\| Lecture 18 - Conclusion/Revision Lecture

	PDF\| CA1 - Manual Sequence Alignment
	PDF\|Promoter.names\|Promoter.data\|ML.names\|ML.data\| CA2 - Data Mining in Bioinformatics

	Lesk, A.M., (2002) Introduction to Bioinformatics, Oxford University Press
	Higgs, P.G., (2005) Bioinformatics and Molecular Evolution, Blackwell Publishing

	Baldi, P., Brunak, S., (2001) Bioinformatics: The Machine Learning Approach, MIT Press
	Keedwell, E., Narayanan, A., (2005) Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems, Wiley