ESG: Extended Similarity Group method for automated protein function prediction

We present here the Extended Similarity Group (ESG) method, which annotates query sequences with Gene Ontology (GO) terms by assigning probability to each annotation computed based on iterative PSI-BLAST searches. Conventionally sequence homology based function annotation methods, such as BLAST, retrieve function information from top hits with a significant score (E-values). In contrast, the PFP method, which we have presented previously, goes one step ahead in utilizing a PSI-BLAST result by considering very weak hits even an E-value of up to 100 and also by incorporating the functional association between GO terms (FAM matrix) computed using term co-occurrence frequencies in the UniProt database. PFP is very successful which is evidenced by the top rank in the function prediction category in CASP7 competition. Our new approach, ESG method, further improves the accuracy of PFP by essentially employing PFP in an iterative fashion. An advantage of ESG is that it is built in a rigorous statistical framework: Unlike PFP method that assigns a weighted score to each GO term, ESG assigns a probability based on weights computed using the E-value of each hit sequence on the path between the original query sequence and the current hit sequence

Finite Element Flow Simulations of the EUROLIFT DLR-F11 High Lift Configuration

This paper presents flow simulation results of the EUROLIFT DLR-F11 multi-element wing configuration, obtained with a highly scalable finite element solver, PHASTA. This work was accomplished as a part of the 2nd high lift prediction workshop. In-house meshes were constructed with increasing mesh density for analysis. A solution adaptive approach was used as an alternative and its effectiveness was studied by comparing its results with the ones obtained with other meshes. Comparisons between the numerical solution obtained with unsteady RANS turbulence model and available experimental results are provided for verification and discussion. Based on the observations, future direction for adaptive research and simulations with higher fidelity turbulence models is outlined.Comment: 52nd Aerospace Sciences Meetin

Microtextures of Laterites and Bauxites Capping Deccan Trap Basalts in Western India

Thirty-five samples of laterites and bauxites representing both the high-level (elevation \u3e 1000 m) and low-level (elevation \u3c 100 m) deposits in western India have been examined by scanning electron microscopy. Megascopically, laterites exhibit vesicular, spongy and pisolitic textures, whereas bauxites display pisolitic, massive and nodular textures. Laterites, as well as bauxites are commonly characterized by framework microtexture produced by a three dimensional arrangement of crystallites. Locally, the luterites and bauxites exhibit crystalline-webby microtexture formed by a web-like arrangement of stacks of lamellar crystals. The individual crystals in the matrix of laterites and bauxites display anhedral forms and they range in size from about 0.5 μm to 20 μm. Crystals larger than 20 μm in size generally occur as linings of the vugs, in channels and veins, and they are usually euhedral. Pisolites and nodules in laterites and bauxites are composed of material generally finer than the material in the matrix around them. Platy morphology is most common for the minerals in laterites and bauxites. Gibbsite occurs in various forms ranging from prismatic, stubby slab-like to lath-shaped crystals. Both high-level and low-level deposits of laterites are characterized by similar textures. The variations in textures of bauxites are also found to be independent of the elevation of the deposits

Tethering of the spinal cord in cervical region in adult male patient

We report a case of a 31-year-old male, came to the medicine department with complains of pain and numbness in upper limb and cervical region. On clinical examination fatty lump was seen in cervical region and muscles had decreased tone. Investigations were done. Magnetic resonance imaging (MRI) showed abnormal mass at C5-C6-C7 level in spinal cord region (A). Initially MRI was taken for cervical region from lateral as well as posterior aspect considering the findings, MRI was repeated to see any involvement in lumbar region (B). No significant abnormality was seen in lumbar region, vertebral bodies showed wedging in the cervical region and fatty mass was seen. The patient was then admitted for this purpose and surgery was planned. Detethering of the spinal cord in cervical region was planned. Myelomeningocele correction was done. Complications of the surgery include cerebrospinal leakage and bladder dysfunction. This patient showed no complications post operatively and was referred to physiotherapy department. The primary goal of the physiotherapist was to prevent secondary complications and to increase the strength of muscles. Special care was taken for cervical region as the patient was post-operative, cervical collar was given and the patient was ambulated on post-operative day 5

Quantification of protein group coherence and pathway assignment using functional association

<p>Abstract</p> <p>Background</p> <p>Genomics and proteomics experiments produce a large amount of data that are awaiting functional elucidation. An important step in analyzing such data is to identify functional units, which consist of proteins that play coherent roles to carry out the function. Importantly, functional coherence is not identical with functional similarity. For example, proteins in the same pathway may not share the same Gene Ontology (GO) terms, but they work in a coordinated fashion so that the aimed function can be performed. Thus, simply applying existing functional similarity measures might not be the best solution to identify functional units in omics data.</p> <p>Results</p> <p>We have designed two scores for quantifying the functional coherence by considering association of GO terms observed in two biological contexts, co-occurrences in protein annotations and co-mentions in literature in the PubMed database. The counted co-occurrences of GO terms were normalized in a similar fashion as the statistical amino acid contact potential is computed in the protein structure prediction field. We demonstrate that the developed scores can identify functionally coherent protein sets, <it>i.e</it>. proteins in the same pathways, co-localized proteins, and protein complexes, with statistically significant score values showing a better accuracy than existing functional similarity scores. The scores are also capable of detecting protein pairs that interact with each other. It is further shown that the functional coherence scores can accurately assign proteins to their respective pathways.</p> <p>Conclusion</p> <p>We have developed two scores which quantify the functional coherence of sets of proteins. The scores reflect the actual associations of GO terms observed either in protein annotations or in literature. It has been shown that they have the ability to accurately distinguish biologically relevant groups of proteins from random ones as well as a good discriminative power for detecting interacting pairs of proteins. The scores were further successfully applied for assigning proteins to pathways.</p

Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

<p>Abstract</p> <p>Background</p> <p>A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance.</p> <p>Results</p> <p>Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, <it>Escherichia coli</it>, <it>Saccharomyces cerevisiae</it>, and <it>Plasmodium falciparum </it>(malaria). The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO) category, <it>i.e. </it>Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the <it>funSim </it>score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the <it>funSim </it>score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted.</p> <p>Conclusion</p> <p>The analyses demonstrate that applying high confidence predictions from PFP can have a significant impact on a researchers' ability to interpret the immense biological data that are being generated today. The newly introduced functional similarity networks of the three organisms show different network properties as compared with the protein-protein interaction networks.</p

In-Depth Performance Evaluation of PFP and ESG Sequence-Based Function Prediction Methods in CAFA 2011 Experiment

Background Many Automatic Function Prediction (AFP) methods were developed to cope with an increasing growth of the number of gene sequences that are available from high throughput sequencing experiments. To support the development of AFP methods, it is essential to have community wide experiments for evaluating performance of existing AFP methods. Critical Assessment of Function Annotation (CAFA) is one such community experiment. The meeting of CAFA was held as a Special Interest Group (SIG) meeting at the Intelligent Systems in Molecular Biology (ISMB) conference in 2011. Here, we perform a detailed analysis of two sequence-based function prediction methods, PFP and ESG, which were developed in our lab, using the predictions submitted to CAFA. Results We evaluate PFP and ESG using four different measures in comparison with BLAST, Prior, and GOtcha. In addition to the predictions submitted to CAFA, we further investigate performance of a different scoring function to rank order predictions by PFP as well as PFP/ESG predictions enriched with Priors that simply adds frequently occurring Gene Ontology terms as a part of predictions. Prediction accuracies of each method were also evaluated separately for different functional categories. Successful and unsuccessful predictions by PFP and ESG are also discussed in comparison with BLAST. Conclusion The in-depth analysis discussed here will complement the overall assessment by the CAFA organizers. Since PFP and ESG are based on sequence database search results, our analyses are not only useful for PFP and ESG users but will also shed light on the relationship of the sequence similarity space and functions that can be inferred from the sequences