Two simulated annealing optimization schemas for rational bézier curve fitting in the presence of noise

Fitting curves to noisy data points is a difficult problem arising in many scientific and industrial domains. Although polynomial functions are usually applied to this task, there are many shapes that cannot be properly fitted by using this approach. In this paper, we tackle this issue by using rational Bézier curves. This is a very difficult problem that requires computing four different sets of unknowns (data parameters, poles, weights, and the curve degree) strongly related to each other in a highly nonlinear way. This leads to a difficult continuous nonlinear optimization problem. In this paper, we propose two simulated annealing schemas (the all-in-one schema and the sequential schema) to determine the data parameterization and the weights of the poles of the fitting curve. These schemas are combined with least-squares minimization and the Bayesian Information Criterion to calculate the poles and the optimal degree of the best fitting Bézier rational curve, respectively. We apply our methods to a benchmark of three carefully chosen examples of 2D and 3D noisy data points. Our experimental results show that this methodology (particularly, the sequential schema) outperforms previous polynomial-based approaches for our data fitting problem, even in the presence of noise of low-medium intensity.This research has been kindly supported by the Computer Science National Program of the Spanish Ministry of Economy and Competitiveness, Project Ref. #TIN2012-30768, Toho University (Funabashi, Japan), and the University of Cantabria (Santander, Spain)

A quaternion-based approach to interference alignment with Alamouti coding

Based on the representation of Alamouti space-time codewords as quaternions, this paper proposes a scheme that combines interference alignment (IA) with Alamouti signals. The proposed formulation allows for a separation of the space-time block coding (to gain spatial diversity) and the IA precoding (to reduce or ideally suppress interference). Although this separation is not necessarily optimal, the splitting of alignment precoding and Alamouti encoding is particularly convenient because it enables the independent optimization of the IA solution using quaternionic versions of standard alternating optimization techniques such as the maximum signal-to-interference-plus-noise algorithm. Some numerical simulations are included to compare the performance of the proposed quaternion IA+Alamouti algorithm with standard IA algorithms in the complex domain as well as with interference cancellation schemes at the receiver side.This work has been supported by the Ministerio de Economía, Industria y Competitividad (MINECO) of Spain, under grants TEC2013-47141-C4-R (RACHEL), TEC2016-75067-C4-4-R (CARMEN), and FPI grant BES-2014-06978

Cell-level pathway scoring comparison with a biologically constrained variational autoencoder

This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in: Pang, J., Niehren, J. (eds) Computational Methods in Systems Biology. CMSB 2023. Lecture Notes in Computer Science, vol 14137. Springer, Cham. Available online at https://doi.org/10.1007/978-3-031-42697-1_

Highly accurate whole-genome imputation of SARS-CoV-2 from partial or low-quality sequences

[Background] The current SARS-CoV-2 pandemic has emphasized the utility of viral whole-genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and, therefore, useless sequences. Viral sequences evolve in the context of a complex phylogeny and different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data.[Results] We have developed the impuSARS application, which takes advantage of the enormous number of SARS-CoV-2 genomes available, using a reference panel containing 239,301 sequences, to produce missing data imputation in viral genomes. ImpuSARS was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing), showing great fidelity when reconstructing the original sequences, recovering the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (<20%).[Conclusions] Imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. ImpuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole-genome sequencing.This work is supported by grant PT17/0009/0006 from the Spanish Ministry of Economy and Competitiveness, COVID-0012–2020 from Consejería de Salud y Familias, Junta de Andalucía, and postdoctoral contract PAIDI2020- DOC_00350 for C.L., from Junta de Andalucía, co-funded by the European Social Fund (FSE) 2014–2020.Peer reviewe

Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival

Objectives: More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain. Methods: A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis. Results: A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins. Conclusions: This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.Ministry of Science and Innovation, Spain (MICINN) Spanish Government PID2020117979RB-I00Instituto de Salud Carlos III European Commission European Commission IMP/00019Junta de Andalucia COVID-0012-2020 PS-2020-342European Social Fund (ESF) 871075Carlos Loucera PAIDI2020-DOC_0035

Documentación tridimensional del patrimonio histórico mediante hibridación de técnicas de visión artificial e ingeniería inversa: el Palacio de la Magdalena en Santander

Este trabajo surgió dentro de la colaboración continuada entre el Grupo de Investigación de Gráficos por Computador y Diseño Geométrico de la Universidad de Cantabria, el Taller de Empleo Nuevas Tecnologías del Ayuntamiento de Santander y el Instituto Urban/Eco de la Università Degli Studi di Napoli – Federico II – de Italia. El proyecto, propuesto por el Ayuntamiento de Santander, consistió en aportar una nueva metodología de trabajo, mucho más acorde con la situación de crisis actual, buscando una reducción importante de los costes derivados de la documentación digital del patrimonio histórico. Además de funcionar como soporte a trabajos de catalogación, conservación y restauración del patrimonio arquitectónico de la ciudad de Santander, aportando documentación fotográfica y gráfica del edificio “Palacio de la Magdalena” mediante la hibridacion de tecnicas fotogrametricas con tecnicas provenientes del campo de la visión artificial. El trabajo se ha enmarcado dentro del Plan Director de la Magdalena. Podemos considerar, a este proyecto de colaboración, como un trabajo de investigación con una importante componente de transmisión tecnológica hacia la sociedad. El producto final de este trabajo es la documentación digital de un edificio considerado como patrimonio histórico, de forma que su fortuito derrumbe o demolición no impida el poder volver a construirlo de forma precisa como si de una réplica se tratase. Es muy importante que no existían planos ni alzados previos de este edificio, más allá de los dibujos originales a mano alzada de los arquitectos del edificio y de unos planos aproximados de la reforma interior realizada en la década de los 90, por ello se ha procedido a documentar métricamente este edificio por ingeniería inversa, de forma que se tengan medidas de todos los elementos arquitectónicos del edificio de forma precisa. El trabajo nace con la intención de ser el prototipo para una nueva metodología de trabajo, combinando diferentes técnicas de tratamiento de imágenes y modelado 3D de objetos de rango cercano, hibridando técnicas fotogramétricas con las provenientes del campo de la visión artificial

CSVS, a crowdsourcing database of the Spanish population genetic variability

The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variabilityworldwide. CSVS is also part of the GA4GH Beacon network.Spanish Ministry of Economy and Competitiveness SAF2017-88908-R PT17/0009/0006 PI19/00321 CIBERER ACCI-06/07/0036 PI14-948 PI171659Regional Government of Madrid, RAREGenomicsCM B2017/BMD3721 B2017/BMD-3721European Union (EU)European Union (EU) 676559University Chair UAM-IIS-FJD of Genomic MedicineRamon Areces Foundatio

Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival

Objectives: More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain. Methods: A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis. Results: A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins. Conclusions: This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.This work was supported by Spanish Ministry of Science and Innovation (grant PID2020- 117979RB-I00), the Instituto de Salud Carlos III (ISCIII), co-funded with European Regional Development Funds (ERDF) (grant IMP/00019), and has also been funded by Consejería de Salud y Familias, Junta de Andalucía (grants COVID-0012-2020 and PS-2020-342) and the postdoctoral contract of Carlos Loucera (PAIDI2020- DOC_00350), co-funded by the European Social Fund (FSE) 2014-2020. ELIXIR-CONVERGE—H2020 (871075).Peer reviewe

Reconstrucción de curvas desde nubes de puntos ruidosos mediante Simulated Annealing

Máster en Matemáticas y Computació