107 research outputs found
Comparative sequence analysis to identify functional elements for functional genomics
No full textComparative sequence analysis is a powerful approach to identify functional elements for functional genomics. For gene prediction, this would mean whether given genomic sequences exhibit significant similarity to some arbitrary region in the genome sequence of an evolutionary related organism or not. Three gene prediction methods were examined to see how they perform on randomly chosen sequences. The focus was on examining the methods rather than data analysis. Thus, the dataset was selected in a flexible manner and may be biased. Our analysis of methods indicated that there are not many differences between recent version of GENEMARK.HMM and GENSCAN in terms of the algorithm used. Both programs use duration HMM and can predict genes and exons on both DNA strands simultaneously. MZEF, on the other hand, uses completely different approach. It employs quadratic discriminant function to distinguish between coding and noncoding regions. The analysis showed that the new generation of programs has substantially better results than the programs analyzed in previous studies. Specifically, GENEMARK.HMM and GENSCAN performed relatively better than MZEF
Data Mining and Knowledge Discovery in Proton Nuclear Magnetic Resonance (1H-NMR) Spectra using Frequency to Information Transformation (FIT)
No full textRecent rapid development of research in the fields of structural genomics and bioinformatics has stressed the need for the development of effective methods of data mining and knowledge extraction from complex and convoluted signals.
In this paper we introduce frequency to information transformation (FIT) as a novel method of extracting information content of complex signals. Because FIT uses a priori knowledge and is a comparative technique, it is well suited for data mining and knowledge discovery from complex data. In this paper, we introduce FIT and compare it to established methods used in automated conditioning and knowledge discovery in proton-nuclear magnetic resonance (1H-NMR) spectra. FIT transformation was applied to a collection of 80 one-dimensional (1D) 1H-NMR spectra of 23 N-linked oligosaccharides.
Three classification methods, namely, cluster analysis, Bayesian analysis and artificial neural networks (ANN) were used to demonstrate the advantages of FIT in information and knowledge extraction in comparison with classical methods such as frequency-based filtering, nonlinear and piecewise linear curve fitting, and correlation coefficient analysis
CCRC-Net: An Internet-Based Spectral Database for Complex Carbohydrates Using Artificial Neural Networks Search Engines
No full textCCRC-Net: an Internet-based spectral database for complex carbohydrates using artificial neural networks search engines
No full textA new combinatorial optimization technique and its applications
No full textIn this thesis, a new global optimization technique, its applications in particular to neural networks, and its implementation on parallel computers are presented and discussed. The algorithm is also compared to other global optimization algorithms such as Gradient descent, Genetic Algorithm and Simulated Annealing. This new optimization technique proved itself worthy of further study after observing its accuracy of convergence, speed of convergence and ease of use. Some of the advantages of this new optimization technique can be summarized as optimizing function does not have to be continuous or differentiable. No random mechanism is used, therefore this algorithm does not inherit the slow speed of random searches. There are no fine-tuning parameters (such as the step rate of G.D. or temperature of S.A.) needed for this technique. This algorithm can be implemented on parallel computers to compensate for the increase in the execution time as the number of dimensions increase
AI in Research
No full textAMA Credit Designation Statement: The Louisiana State University School of Medicine, New Orleans designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
NCPD Credit Designation Statement: Nursing participants may earn 1.0 NCPD contact hours. Each nursing participant must be present for the entire session for which NCPD contact hours are requested and must complete an evaluation of the session to receive credit
An Investigation into the Elements of Lyrics in the Poem of Homay and Homayoun by Khaju Kermani
No full textLyric includes a wide range of subjects and poetic formats. Specifically, it is a type of poem in which the element of emotion is dominant and naturally it has some components that have made it different from other types. In the present study, the author investigated the indicators of lyrics in the story of Homay and Homayoun by Khaju Kermani and the poet pays attention to rhetorical principles and the relationship with the audience. Components that this study has been written based on them are the personalization of "I" in lyrics and introspection, being romantic-mystical, compounds of lyrics, descriptions, and metaphors, investigation of battles and banquets, etc. which is matched by expressing some examples of Khaju's poems. The general purpose of the research is how these components are manifested in Homay and Homayoun? The result of the research is that; the mighty poet has paid attention to the form and meaning and the way they are used and their impact on the reader. This literal type enjoys a great deal of lyrics value due to the usage of battle and mythological elements by Khaju and ethical points(doctrinal) that are specific to other types, and the emergence of lyrics indicators is outstanding in the way that it covers epic and ethical indicators. The imagination power of the poet and using these features have turned the work into a lyric and made it a special one
DataDock: An Open Source Data Hub for Research
No full textEvery research project necessitates data, often requiring sharing and collaborative review within a team. However, there is a dearth of good open-source data sharing and reviewing services. Existing file-sharing services generally mandate paid subscriptions for increased storage or additional members, diverting research funds from addressing the core research problem that a lab is attempting to work on. Moreover, these services often lack direct features for reviewing or commenting on data quality, a vital part of ensuring high quality data generation. In response to these challenges, we present DataDock, a specialized file transfer service crafted for specifically for researchers. DataDock operates as an application hosted on a research lab server. This design ensures that, with access to a machine and an internet connection, teams can facilitate file storage, transfer, and review without incurring extra costs. Being an open-source project, DataDock can be customized to suit the unique requirements of any research team, and is able to evolve to meet the needs of the research community. We also note that there are no limitations with respect to what data can be shared, downloaded, or commented on. As DataDock is agnostic to the file type, it can be used in any field from bioinformatics to particle physics; as long as it can be stored in a file, it can be shared. We open source the code here: https://github.com/lxaw/DataDock7 pages, 6 figures, submitted and in review at The 2024 World Congress in Computer Science, Computer Engineering, And Applied Computing (CSCE
Dihedral Angle Adherence: Evaluating Protein Structure Predictions in the Absence of Experimental Data
No full textDetermining the 3D structures of proteins is essential in understanding their behavior in the cellular environment. Computational methods of predicting protein structures have advanced, but assessing prediction accuracy remains a challenge. The traditional method, RMSD, relies on experimentally determined structures and lacks insight into improvement areas of predictions. We propose an alternative: analyzing dihedral angles, bypassing the need for the reference structure of an evaluated protein. Our method segments proteins into amino acid subsequences and searches for matches, comparing dihedral angles across numerous proteins to compute a metric using Mahalanobis distance. Evaluated on many predictions, our approach correlates with RMSD and identifies areas for prediction enhancement. This method offers a promising route for accurate protein structure prediction assessment and improvement.6 pages, 7 figures. Accepted to and to be published by BIOCOMP\u2724, The 25th International Conference on Bioinformatics & Computational Biolog
Multiple Structure Alignment with msTALI
No full textBackground
Multiple structure alignments have received increasing attention in recent years as an alternative to multiple sequence alignments. Although multiple structure alignment algorithms can potentially be applied to a number of problems, they have primarily been used for protein core identification. A method that is capable of solving a variety of problems using structure comparison is still absent. Here we introduce a program msTALI for aligning multiple protein structures. Our algorithm uses several informative features to guide its alignments: torsion angles, backbone Cα atom positions, secondary structure, residue type, surface accessibility, and properties of nearby atoms. The algorithm allows the user to weight the types of information used to generate the alignment, which expands its utility to a wide variety of problems. Results
msTALI exhibits competitive results on 824 families from the Homstrad and SABmark databases when compared to Matt and Mustang. We also demonstrate success at building a database of protein cores using 341 randomly selected CATH domains and highlight the contribution of msTALI compared to the CATH classifications. Finally, we present an example applying msTALI to the problem of detecting hinges in a protein undergoing rigid-body motion. Conclusions
msTALI is an effective algorithm for multiple structure alignment. In addition to its performance on standard comparison databases, it utilizes clear, informative features, allowing further customization for domain-specific applications. The C++ source code for msTALI is available for Linux on the web athttp://ifestos.cse.sc.edu/mstali webcite
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