2022 IEEE 4th International Conference on BioInspired Processing (BIP)最新文献_第2页

miR-124-2, miR-92-A1 and miR-372 regulate differential gene expression in a mathematical model of the progression of ductal carcinoma in situ (DCIS) to microinvasive breast cancer (MIBC) miR-124-2、miR-92-A1和miR-372在导管原位癌(DCIS)向微浸润性乳腺癌(MIBC)进展的数学模型中调控差异基因表达

2022 IEEE 4th International Conference on BioInspired Processing (BIP) Pub Date : 2022-11-15 DOI: 10.1109/BIP56202.2022.10032474

Chinchilla-Monge Ricardo, Chaves-Chaves Noe, Mora-Rodriguez Rodrigo

{"title":"miR-124-2, miR-92-A1 and miR-372 regulate differential gene expression in a mathematical model of the progression of ductal carcinoma in situ (DCIS) to microinvasive breast cancer (MIBC)","authors":"Chinchilla-Monge Ricardo, Chaves-Chaves Noe, Mora-Rodriguez Rodrigo","doi":"10.1109/BIP56202.2022.10032474","DOIUrl":"https://doi.org/10.1109/BIP56202.2022.10032474","url":null,"abstract":"Breast cancer is a widely studied genetic disease that has a clear division between an initial stage, starting with the atypical ductal hyperplasia progressing to ductal carcinoma in situ and ending, although not necessarily, with invasive breast cancer. Nonetheless, if the invasive breast cancer has only colonized less than 1mm of healthy estroma it is classified as microinvasive breast carcinoma. We hypothesized that differentially expressed genes in tumoral cells of early carcinoma are regulated by specific miRNAs and TF that stimulate the progression to an invasive stage. Our main goal was to reach a minimal model that can explain this behavior and identify promising miRNA targets with therapeutic potential. Using BioNetUCR and COPASI for a systems biology approach, we identified miRNAs miR-372, miR-124-2 and miR-92-A1 that modify the differential gene expression in MIBC stage. These miRNAs have potential as therapeutic targets for future treatment strategies by suppressing the transition from DCIS to IBC. There are few studies about DCIS to MIBC transition, but with this computational approach we present one of the first in silico models for this type of cell transition.","PeriodicalId":161872,"journal":{"name":"2022 IEEE 4th International Conference on BioInspired Processing (BIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131991963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards Text Simplification in Spanish: A Brief Overview of Deep Learning Approaches for Text Simplification 迈向西班牙语文本简化:文本简化的深度学习方法概述

2022 IEEE 4th International Conference on BioInspired Processing (BIP) Pub Date : 2022-11-15 DOI: 10.1109/BIP56202.2022.10032482

M. Romero, Saul Calderon-Ramirez, M. Solis, Nelson Perez-Rojas, M. Chacón-Rivas, Horacio Saggion

{"title":"Towards Text Simplification in Spanish: A Brief Overview of Deep Learning Approaches for Text Simplification","authors":"M. Romero, Saul Calderon-Ramirez, M. Solis, Nelson Perez-Rojas, M. Chacón-Rivas, Horacio Saggion","doi":"10.1109/BIP56202.2022.10032482","DOIUrl":"https://doi.org/10.1109/BIP56202.2022.10032482","url":null,"abstract":"Text simplification refers to the transformation of a specific source text into a target text aiming to increase understanding and readability for one or more specific audiences. This task demands large human efforts and specialized knowledge, which makes the usage of automated or semi-automated computational approaches appealing. The rise of deep learning as an unifying paradigm between seemingly different fields as image analysis, sound processing and natural language processing has considerably influenced the current state of the art approaches for automatic text simplification. Therefore, in this work, we focus on the study of deep learning based state of the art methods for automatic text simplification in the Spanish language. For this end, we first disentangle the different tasks which can be addressed in order to yield a simplified text in general. Later we review the latest deep learning-based approaches, along with the main datasets and performance metrics used in the field. We also describe approaches to deal with small datasets and technical words. Finally, we describe some lessons to build accurate automatic text simplification systems in Spanish, as in this language there is a noticeable shortage of work for text simplification.","PeriodicalId":161872,"journal":{"name":"2022 IEEE 4th International Conference on BioInspired Processing (BIP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124322743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

mi-RNA129-1 and mi-RNA24-2 as regulators of over-expressed genes in lung typical carcinoid tumors: Potential targets for molecular therapy mi-RNA129-1和mi-RNA24-2作为肺典型类癌过度表达基因的调节因子:分子治疗的潜在靶点

2022 IEEE 4th International Conference on BioInspired Processing (BIP) Pub Date : 2022-11-15 DOI: 10.1109/BIP56202.2022.10032481

Abbas-Chakhtoura Jad, Chinchilla-Monge Ricardo, Mora-Rodriguez Rodrigo

{"title":"mi-RNA129-1 and mi-RNA24-2 as regulators of over-expressed genes in lung typical carcinoid tumors: Potential targets for molecular therapy","authors":"Abbas-Chakhtoura Jad, Chinchilla-Monge Ricardo, Mora-Rodriguez Rodrigo","doi":"10.1109/BIP56202.2022.10032481","DOIUrl":"https://doi.org/10.1109/BIP56202.2022.10032481","url":null,"abstract":"Lung carcinoid tumors are malignant neuroendocrine neoplasms that account for less than 2% of all lung malignancies and include two histological types: typical and atypical carcinoid tumors. Typical carcinoid tumors do not include areas of necrosis and show less than 2 mitotic figures within 10 high grade fields. On the molecular level, carcinoid tumors present alterations in gene MEN1 as well as a high expression of genes ASCL1 and EIF1AX. We report a systems biology approach using BioNetUCR and Copasi in addition to Cytoscape to identify mi-RNA regulators of the most important altered genes in typical pulmonary carcinoid tumors. The final adjusted and reduced interaction network of our genes of interest included: 3 genes 12 transcription factors and 7 mi-RNAs, leading to a total of 22 nodes and 53 edges. Analysis with Copasi showed that MIR24-2 regulates the expression of MEN1 and MIR129-1 regulates the expression of AIF1AX. Those mi-RNAs could be potential targets for molecular therapy in patients with typical carcinoid tumor of lung.","PeriodicalId":161872,"journal":{"name":"2022 IEEE 4th International Conference on BioInspired Processing (BIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124347757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of Nextera XT and Collibri ES library preparation kits: from wet lab to bioinformatics analysis Nextera XT和Collibri ES文库制备试剂盒的比较:从湿实验室到生物信息学分析

2022 IEEE 4th International Conference on BioInspired Processing (BIP) Pub Date : 2022-11-15 DOI: 10.1109/BIP56202.2022.10032483

Layla Nassar-Miguez, Andrés Flores-Cruz, Ivannia Atmetlla-Salazar, Rebeca Campos-Sánchez

引用次数: 0

miR-let-7a-2, miR103a-2 and CREB1-TF as therapeutic targets to regulate the transcription of DISC1 and PDE4D in the transcriptional regulation pathway by DISC1/ATF4 complex miR-let-7a-2、miR103a-2和CREB1-TF作为治疗靶点，通过DISC1/ATF4复合物在转录调控通路中调控DISC1和PDE4D的转录

2022 IEEE 4th International Conference on BioInspired Processing (BIP) Pub Date : 2022-11-15 DOI: 10.1109/BIP56202.2022.10032479

Esteban Jose Rodriguez Rodriguez, R. Mora-Rodríguez

{"title":"miR-let-7a-2, miR103a-2 and CREB1-TF as therapeutic targets to regulate the transcription of DISC1 and PDE4D in the transcriptional regulation pathway by DISC1/ATF4 complex","authors":"Esteban Jose Rodriguez Rodriguez, R. Mora-Rodríguez","doi":"10.1109/BIP56202.2022.10032479","DOIUrl":"https://doi.org/10.1109/BIP56202.2022.10032479","url":null,"abstract":"Disrupted In Schizophrenia 1 (DISC1) is considered a multifunctional protein implicated in various signaling pathways with neurological relevant outcomes, with the Disrupted In Schizophrenia 1/Activating Transcription Factor 4 (DISC1/ATF4) transcriptional regulation pathway being a pathway of interest since it regulates Phosphodiesterase 4D (PDE4D) transcription. Alterations in the transcription levels of DISC1 and PDE4D have been implicated in neurodegenerative processes and the identification of therapeutic targets that regulate these processes can be of great help to promote neuroprotective processes. By using a System Biology approach, we created a mathematical model of the transcriptional regulation of the DISC1/ATF4 pathway and using this model we conducted in-silico experiments to identify potential therapeutic targets with robust control on the network. As a result, miR-let-7a-2 is reported as a transcriptional regulator of DISC1 as well as miR103-a2 and CREB1-TF as transcriptional regulators of the PDE4D. These three regulators are identified as in-silico therapeutic targets to promote neuroprotective processes against neurodegenerative mental disorders.","PeriodicalId":161872,"journal":{"name":"2022 IEEE 4th International Conference on BioInspired Processing (BIP)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132894385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recognition of grammatical classes of overt speech using electrophysiological signals and machine learning 利用电生理信号和机器学习识别显性言语的语法类别

2022 IEEE 4th International Conference on BioInspired Processing (BIP) Pub Date : 2022-11-15 DOI: 10.1109/BIP56202.2022.10032476

Samanta J. Barrientos Rojas, Raquel Ramirez-Valencia, Denise Alonso-Vazquez, Ricardo Caraza, Hector R. Martinez, O. Mendoza-Montoya, J. Antelis

{"title":"Recognition of grammatical classes of overt speech using electrophysiological signals and machine learning","authors":"Samanta J. Barrientos Rojas, Raquel Ramirez-Valencia, Denise Alonso-Vazquez, Ricardo Caraza, Hector R. Martinez, O. Mendoza-Montoya, J. Antelis","doi":"10.1109/BIP56202.2022.10032476","DOIUrl":"https://doi.org/10.1109/BIP56202.2022.10032476","url":null,"abstract":"In this paper, we propose the use of overt speech in grammatical class classification using electroencephalography (EEG) and electromyography (EMG) signals as a first approach to attempt speech decoding in patients with bulbar amyotrophic lateral sclerosis (ALS). The work was carried out with 4 healthy participants, 32 EEG channels evenly distributed over the scalp and 4 EMG channels located in the zygomaticus major and triangular muscles were recorded during Spanish word production. Different classification algorithms, including a neural network, were evaluated in two groups of grammatical classes: adverbs vs. nouns. In EEG signals, 92.6±2.09% accuracy was achieved, while with EMG, 94.84±4.71%. These results show that it is possible to recognize grammatical classes in overt speech using EEG or EMG signals. The best performance in the EEG and EMG signals was obtained with the linear SVM classifier. Based on the classification accuracy of each class in each of the classification models, it is concluded that it is more convenient to use EMG signals in overt speech concerning EEG; however, if we want to decode the attempted speech in ALS patients using non-invasive methods, it is necessary to use the information provided by the EEG signals.","PeriodicalId":161872,"journal":{"name":"2022 IEEE 4th International Conference on BioInspired Processing (BIP)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130501977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images 基于自动阈值法改进半监督深度学习的胸部x线图像COVID-19检测非分布数据处理

2022 IEEE 4th International Conference on BioInspired Processing (BIP) Pub Date : 2022-11-03 DOI: 10.1109/BIP56202.2022.10032469

Isaac Benavides-Mata, Saúl Calderón Ramírez

{"title":"Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images","authors":"Isaac Benavides-Mata, Saúl Calderón Ramírez","doi":"10.1109/BIP56202.2022.10032469","DOIUrl":"https://doi.org/10.1109/BIP56202.2022.10032469","url":null,"abstract":"Semi-supervised learning (SSL) leverages both labeled and unlabeled data for training models when the labeled data is limited and the unlabeled data is vast. Frequently, the unlabeled data is more widely available than the labeled data, hence this data is used to improve the level of generalization of a model when the labeled data is scarce. However, in real-world settings unlabeled data might depict a different distribution than the labeled dataset distribution. This is known as distribution mismatch. Such problem generally occurs when the source of unlabeled data is different from the labeled data. For instance, in the medical imaging domain, when training a COVID-19 detector using chest X-ray images, different unlabeled datasets sampled from different hospitals might be used. In this work, we propose an automatic thresholding method to filter out-of-distribution data in the unlabeled dataset. We use the Mahalanobis distance between the labeled and unlabeled datasets using the feature space built by a pre-trained Image-net Feature Extractor (FE) to score each unlabeled observation. We test two simple automatic thresholding methods in the context of training a COVID-19 detector using chest X-ray images. The tested methods provide an automatic manner to define what unlabeled data to preserve when training a semi-supervised deep learning architecture.","PeriodicalId":161872,"journal":{"name":"2022 IEEE 4th International Conference on BioInspired Processing (BIP)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114168094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0