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Unsupervised Word Sense Disambiguation Using Alpha-Beta Associative Memories

Sulema Torres-Ramos, Israel Román-Godínez, E. Gerardo Mendizabal-Ruiz
2016 POLIBITS Research Journal on Computer Science and Computer Engineering With Applications  
Index Terms-Word sense disambiguation, simple Lesk algorithm, Alpha-Beta associative memories.  ...  This paper presents an algorithm that uses Alpha-Beta associative memory type Max and Min to measure a given ambiguous word's meaning in relation to its context, assigning to the word the meaning that  ...  In particular, Alpha-Beta associative memories have been proven to be a powerful tool for pattern recognition tasks when used in various scientific and technologic applications, such as the classification  ... 
doi:10.17562/pb-54-6 fatcat:go5khn4esbcxbonugsmqd7bddm

TOPS++FATCAT: Fast flexible structural alignment using constraints derived from TOPS+ Strings Model

Mallika Veeramalai, Yuzhen Ye, Adam Godzik
2008 BMC Bioinformatics  
Protein structure analysis and comparison are major challenges in structural bioinformatics.  ...  of rapid database searches.  ...  Acknowledgements This research was supported by NIH grant P20 GM076221 (Joint Center for Molecular Modeling). We would like to thank TOPS project for TOPS+ resources.  ... 
doi:10.1186/1471-2105-9-358 pmid:18759993 pmcid:PMC2553092 fatcat:ieiztm5qqravrevqeh7hetiq5y

GOR Method for Protein Structure Prediction using Cluster Analysis

Rajbir singh, Neha Jain, Dheeraj Pal Kaur
2013 International Journal of Computer Applications  
The analysis and interpretation of bioinformatics database which includes various types of data such as nucleotide and amino acid sequences, protein domains, and protein structures is an important step  ...  The emphasis here is on the use of computers because most of the tasks involved in genomic data analysis are highly repetitive or mathematically complex.  ...  They do not have even patterns like alpha-helices and beta-sheets and they could be any other part of the protein structure.  ... 
doi:10.5120/12702-9495 fatcat:hddf7hk6z5cbjklkt4v5w2ycna

Global sequence properties for superfamily prediction: a machine learning approach

Richard Jb. Dobson, Patricia B Munroe, Mark J Caulfield, Mansoor Saqi
2009 Journal of Integrative Bioinformatics  
We show machine learning models used to predict categories within the SCOP database can be significantly improved via a simple sequence enrichment step.  ...  In this study, a simple set of sequence attributes based on physicochemical and predicted structural characteristics were used as input to machine learning methods.  ...  This work was funded by the MRC Programme Grant No. G9521010 (British Genetics of Hypertension [BRIGHT] study). Disclosure Statement No commercial associations reported by any authors.  ... 
doi:10.1515/jib-2009-109 fatcat:j4vjketebjhw7le3w34ta2den4

Application of the Lernmatrix tau[9] to the classification of patterns in medical datasets

2020 International Journal of Advanced Trends in Computer Science and Engineering  
The databases used in this work are KEEL and ICU.  ...  The information is disease-classified, has entering patterns and test patterns for intelligent computing algorithms to use it and measure their performance.  ...  ACKNOWLEDGEMENT The authors want to thank the Universidad Politécnica de Pachuca, the Instituto Politécnico Nacional, Mexico (SecretaríaAcadémica, EST, CIDETEC, COFAA), the CONACYT and SNI for their support in  ... 
doi:10.30534/ijatcse/2020/228952020 fatcat:bxco5ni6mvdg7m4nk655hfwbhu

Chemoinformatics and structural bioinformatics in OCaml

Francois Berenger, Kam Y. J. Zhang, Yoshihiro Yamanishi
2019 Journal of Cheminformatics  
In this article, we share our experience in prototyping chemoinformatics and structural bioinformatics software in OCaml.  ...  Finally, tools and methods useful when prototyping scientific software in OCaml are given.  ...  Some of the computing power used in this study was provided by RIKEN ACCC, on the Hokusai Large Memory Application Computing Server.  ... 
doi:10.1186/s13321-019-0332-0 pmid:30719579 pmcid:PMC6689879 fatcat:46vtz2gz35a57nngeqckfyg22i

Reporting and connecting cell type names and gating definitions through ontologies

James A. Overton, Randi Vita, Patrick Dunn, Julie G. Burel, Syed Ahmad Chan Bukhari, Kei-Hoi Cheung, Steven H. Kleinstein, Alexander D. Diehl, Bjoern Peters
2019 BMC Bioinformatics  
Such techniques classify cells into populations based on the detection of a pattern of markers.  ...  We used a large set of such gating definitions and corresponding cell types submitted by different investigators into ImmPort, a central database for immunology studies, to examine the ability to parse  ...  Availability of data and materials All data are available in the ImmPort database in raw format, and in processed format as used in this articles from the authors upon request.  ... 
doi:10.1186/s12859-019-2725-5 pmid:31272390 pmcid:PMC6509839 fatcat:vpfacm2ijjehxjss2sk4qktmgi

QIIME 2 Enables Comprehensive End‐to‐End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data

Mehrbod Estaki, Lingjing Jiang, Nicholas A. Bokulich, Daniel McDonald, Antonio González, Tomasz Kosciolek, Cameron Martino, Qiyun Zhu, Amanda Birmingham, Yoshiki Vázquez‐Baeza, Matthew R. Dillon, Evan Bolyen (+2 others)
2020 Current Protocols in Bioinformatics  
We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses-e.g., improving taxonomic classification  ...  birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet.  ...  Many microbial ecology studies use alpha diversity (within-sample richness and/or evenness) and beta diversity (between-sample dissimilarity) to reveal patterns in the microbial diversity in a set of samples  ... 
doi:10.1002/cpbi.100 pmid:32343490 fatcat:i2ssiyaxvbartoaarja5p7f5dq

Systematic processing of ribosomal RNA gene amplicon sequencing data

Julien Tremblay, Etienne Yergeau
2019 GigaScience  
Because of its low cost, robust databases, and established bioinformatic workflows, sequencing of 16S/18S/ITS ribosomal RNA (rRNA) gene amplicons, which provides a marker of choice for phylogenetic studies  ...  Moreover, a wealth of stand-alone software packages that perform specific targeted bioinformatic tasks are increasingly accessible, and finding a way to easily integrate these applications in a pipeline  ...  The RDP database (not to be confused with the RDP classifier software) was also built in a similar manner.  ... 
doi:10.1093/gigascience/giz146 pmid:31816087 pmcid:PMC6901069 fatcat:qvu2rgryvjhannlmkccdryh2xi

A multi-task deep-learning system for predicting membrane associations and secondary structures of proteins [article]

BIAN LI, Jeffrey Mendenhall, John Anthony Capra, Jens Meiler
2020 bioRxiv   pre-print
The new method, Membrane Association and Secondary Structures of Proteins (MASSP) predictor, uses multi‐tiered neural networks that incorporate recent innovations in machine learning.  ...  We curated a non-redundant data set consisting of 54 bitopic, 241 multi-spanning TM-alpha, 77 TM-beta, and 372 soluble proteins, respectively for training and testing MASSP.  ...  The second predictor is a long 691 short-term memory (LSTM) recurrent neural network-based sequence-level classifier 692 trained to predict the protein class (bitopic, TM-alpha, TM-beta, soluble) Residue  ... 
doi:10.1101/2020.12.02.409045 fatcat:3ujlkwaelrebrdrgzvuhsd2smm

Global sequence properties for superfamily prediction: a machine learning approach

Richard J B Dobson, Patricia B Munroe, Mark J Caulfield, Mansoor A S Saqi
2009 Journal of Integrative Bioinformatics  
These methods were used to predict membership to 24 and 49 large and diverse protein superfamiles from the SCOP database.  ...  We show machine learning models used to predict categories within the SCOP database can be significantly improved via a simple sequence enrichment step.  ...  This work was funded by the MRC Programme Grant No. G9521010 (British Genetics of Hypertension [BRIGHT] study). Disclosure Statement No commercial associations reported by any authors.  ... 
doi:10.2390/biecoll-jib-2009-109 pmid:20134076 fatcat:ncjavyem4rhztew7upqlyopta4

VAMPS: a website for visualization and analysis of microbial population structures

Susan M Huse, David B Mark Welch, Andy Voorhis, Anna Shipunova, Hilary G Morrison, A Eren, Mitchell L Sogin
2014 BMC Bioinformatics  
VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.  ...  VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret  ...  Acknowledgements Special thanks to both Richard Fox for providing the system administration support at the Bay Paul Center necessary to keep the VAMPS website up and running and to Philip Neal who participated in  ... 
doi:10.1186/1471-2105-15-41 pmid:24499292 pmcid:PMC3922339 fatcat:k34klccdyzcwtn4yj57kudexaa

Transcriptome profiling in engrailed-2 mutant mice reveals common molecular pathways associated with autism spectrum disorders

Paola Sgadò, Giovanni Provenzano, Erik Dassi, Valentina Adami, Giulia Zunino, Sacha Genovesi, Simona Casarosa, Yuri Bozzi
2013 Molecular Autism  
Furthermore, when directly compared to the repository of the SFARI database, our differentially expressed genes in the hippocampus showed enrichment of ASD-associated genes significantly higher than previously  ...  Conclusions: Despite the limited number of animals used in the study, our bioinformatic analysis indicates the En2 −/− mouse is a valuable tool for investigating molecular alterations related to ASD.  ...  To verify the tissue-expression pattern of the samples, we first classified the differentially expressed genes based on their tissue expression (P <0.05, calculated using Benjamini multiple testing correction  ... 
doi:10.1186/2040-2392-4-51 pmid:24355397 pmcid:PMC3896729 fatcat:qmac3fcgczgdtmz7bwkkqq4gim

Classifi cation of Protein Structural Classes using Isoluecine and Lysine Amino Acids

K. Manikandakumar, K. Gokul Raj, R. Srikumar, S. Muthukumaran
2010 Journal of Proteomics & Bioinformatics  
by Beta protein classes with the fl at protein primary structure only.  ...  This technique is tested over 40801 (inclusive of side chains, i.e., chain A, B, 1, 2, etc) proteins belonging to 67 different families randomly selected from All Alpha, All Beta, Alpha plus Beta and Alpha  ...  We used Microsoft Excel packages for calculations and generating figures. Then we have manually classified for all alpha, all beta, alpha plus beta and alpha by beta structural classes.  ... 
doi:10.4172/jpb.1000143 fatcat:eeaiqh4lfveb5foybxyuggm5hu

Multiple Attractor Cellular Automata (MACA) for Addressing Major Problems in Bioinformatics [article]

Pokkuluri Kiran Sree, Inampudi Ramesh Babu, SSSN Usha Devi Nedunuri
2013 arXiv   pre-print
CA has grown as potential classifier for addressing major problems in bioinformatics.  ...  Lot of bioinformatics problems like predicting the protein coding region, finding the promoter region, predicting the structure of protein and many other problems in bioinformatics can be addressed through  ...  Furthermore, proteins can be classified according to their structural elements, specifically their alpha helix and beta sheet content.  ... 
arXiv:1310.4495v1 fatcat:7vk4rberangu3ptgkwa3cyqfbm
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