Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

/pdf/bioinformatics-enrichment-tools-paths-toward-the-2yo1xl3r2j.pdf

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

New evidence and consensus has led to further revision of the McDonald Criteria for diagnosis of multiple sclerosis. The use of imaging for demonstration of dissemination of central nervous system lesions in space and time has been simplified, and in some circumstances dissemination in space and time can be established by a single scan. These revisions simplify the Criteria, preserve their diagnostic sensitivity and specificity, address their applicability across populations, and may allow earlier diagnosis and more uniform and widespread use.

/pdf/diagnostic-criteria-for-multiple-sclerosis-2010-revisions-to-24iph50480.pdf

Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria

https://www.bioinf.uni-leipzig.de/Leere/WS1516/SeqAnalGen/T-Coffee.pdf

T-Coffee: A novel method for fast and accurate multiple sequence alignment.

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era

/pdf/metascape-provides-a-biologist-oriented-resource-for-the-1ovoy8ih4d.pdf

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

The Biochemical Algorithms Library (BALL) is a comprehensive rapid application development framework for structural bioinformatics. It provides an extensive C++ class library of data structures and algorithms for molecular modeling and structural bioinformatics. Using BALL as a programming toolbox does not only allow to greatly reduce application development times but also helps in ensuring stability and correctness by avoiding the error-prone reimplementation of complex algorithms and replacing them with calls into the library that has been well-tested by a large number of developers. In the ten years since its original publication, BALL has seen a substantial increase in functionality and numerous other improvements. Here, we discuss BALL's current functionality and highlight the key additions and improvements: support for additional file formats, molecular edit-functionality, new molecular mechanics force fields, novel energy minimization techniques, docking algorithms, and support for cheminformatics. BALL is available for all major operating systems, including Linux, Windows, and MacOS X. It is available free of charge under the Lesser GNU Public License (LPGL). Parts of the code are distributed under the GNU Public License (GPL). BALL is available as source code and binary packages from the project web site at http://www.ball-project.org
 . Recently, it has been accepted into the debian project; integration into further distributions is currently pursued.

/pdf/ball-biochemical-algorithms-library-1-3-bvf0f3lgyn.pdf

BALL--biochemical algorithms library 1.3.

MOTIVATION Understanding the biochemistry of a newly sequenced organism is an essential task for post-genomic analysis. Since, however, genome and array data grow much faster than biochemical information, it is necessary to infer reactions by comparative analysis. No integrated and easy to use software tool for this purpose exists as yet. RESULTS We present a new software system--BioMiner--for analyzing and visualizing biochemical pathways and networks. BioMiner is based on a new comprehensive, extensible and reusable data model--BioCore--which can be used to model biochemical pathways and networks. As a first application we present PathFinder, a new tool predicting biochemical pathways by comparing groups of related organisms based on sequence similarity. We successfully tested PathFinder with a number of experiments, e.g. the well studied glycolysis in bacteria. Additionally, an application called PathViewer for the visualization of metabolic networks is presented. PathViewer is the first application we are aware of which supports the graphical comparison of metabolic networks of different organisms. AVAILABILITY http://www.zbi.uni-saarland.de/chair/projects/BioMiner SUPPLEMENTARY INFORMATION Additional information on experimental results can be found on our web site.

/pdf/biominer-modeling-analyzing-and-visualizing-biochemical-476ke46eoo.pdf

BioMiner--modeling, analyzing, and visualizing biochemical pathways and networks.

https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/25787/1/KnutReinert_ProfDrKurtMehlhorn.pdf

A polyhedral approach to sequence alignment problems

We consider a branch-and-cut approach for solving the multiple sequence alignment problem, which is a central problem in computational biology. We propose a general model for this problem in which arbitrary gap costs are allowed. An interesting aspect of our approach is that the three (exponentially large) classes of natural valid inequalities that we consider turn out to be both facet-defining for the convex hull of integer solutions and separable in polynomial time. Both the proofs that these classes of valid inequalities are facet-defining and the description of the separation algorithms are far from trivial. Experimental results on several benchmark instances show that our method outperforms the best tools developed so far, in that it produces alignments that are better from a biological point of view. A noteworthy outcome of the results is the effectiveness of using branch-and-cut with only a carefully-selected subset of the variables as a heuristic.

A branch-and-cut algorithm for multiple sequence alignment

Autoantibodies against self-antigens have been associated not only with autoimmune diseases, but also with cancer and are even found in healthy individuals. The mechanism causing the autoantibody response remains elusive for the majority of the immunogenic antigens. To deepen the understanding of autoantibody responses, we ask whether natural-occurring, autoimmunity-associated and tumor-associated antigens have structural or biological features related to the immune response. To this end, we have carried out the most comprehensive in-silicio study of different groups of autoantigens including large antigen sets identified by our groups combined with publicly available antigen sets. We found evidence for an enrichment of genes with a larger exon length increasing the probability of the occurrence of potential immunogenic features such as mutations, SNPs, immunogenic sequence patterns and structural epitopes, or alternative splicing events. While SNPs seem to play a more central role in autoimmunity, somatic mutations seem to be stronger enriched in tumor-associated antigens. In addition, antigens of autoimmune diseases are different from other antigen sets in that they appear preferentially secreted, have frequently an extracellular location, and they are enriched in pathways associated with the immune system. Furthermore, for autoantibodies in general, we found enrichment of sequence-based properties including coiled-coils motifs, ELR motifs, and Zinc finger DNA-binding motifs. Moreover, we found enrichment of proteins binding to proteins or nucleic acids including RNA and enrichment of proteins that are part of ribosome or spliceosome. Both, homologies to proteins of other species and an enrichment of ancient protein domains indicate that immunogenic proteins are evolutionary conserved and that mimicry might play a central role. Our results provide evidence that proteins which i) are evolutionary conserved, ii) show specific sequence motifs, and iii) are part of cellular structures show an increased likelihood to become autoimmunogenic.

/pdf/immunogenicity-of-autoantigens-3n4y5844y4.pdf

Hans-Peter Lenhof

Papers

BALL--biochemical algorithms library 1.3.

BioMiner--modeling, analyzing, and visualizing biochemical pathways and networks.

A polyhedral approach to sequence alignment problems

A branch-and-cut algorithm for multiple sequence alignment

Immunogenicity of autoantigens