標題: Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 17th International M Davide Chicco,Angelo Facchiano,Paolo Cazzanig [打印本頁] 作者: 五個 時間: 2025-3-21 17:23
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics影響因子(影響力)
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics影響因子(影響力)學科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics網(wǎng)絡公開度
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics網(wǎng)絡公開度學科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics被引頻次
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics被引頻次學科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics年度引用
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics年度引用學科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics讀者反饋
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics讀者反饋學科排名
作者: Hay-Fever 時間: 2025-3-21 22:11
Biochemische Individualit?t und Gichtects showing PLM (mainly restless legs syndrome patients). Despite its many simplifying assumptions—the strongest being the stationarity of the neural processes during night sleep—the model simulations are in remarkable agreement with the polysomnographically recorded data.作者: 入伍儀式 時間: 2025-3-22 00:44
https://doi.org/10.1007/978-3-642-94920-3 addition, automatic averaging and aligning of 2D-CNN gradient-based images is applied and shown to improve its biological meaning. The proposed model predicts soft biological brain ageing indicators with a six-class-balanced accuracy of . by using the anagraphic age of 1100 healthy subjects in comparison to their brain scans.作者: Dendritic-Cells 時間: 2025-3-22 07:15
Real-Time Automatic Plankton Detection, Tracking and Classification on Raw Hologram,ideos of raw holograms. Experiments show that our pipeline based on YOLOv5 and SORT is fast (44 FPS) and can accurately detect and identify the plankton among 13 classes (97.6% mAP@0.5, 92% MOTA). Our method can be implemented to detect and count other microscopic objects in raw holograms.作者: 邊緣 時間: 2025-3-22 10:52
The First , Model of Leg Movement Activity During Sleep,ects showing PLM (mainly restless legs syndrome patients). Despite its many simplifying assumptions—the strongest being the stationarity of the neural processes during night sleep—the model simulations are in remarkable agreement with the polysomnographically recorded data.作者: interlude 時間: 2025-3-22 15:23
,Soft Brain Ageing Indicators Based on?Light-Weight LeNet-Like Neural Networks and?Localized 2D Brai addition, automatic averaging and aligning of 2D-CNN gradient-based images is applied and shown to improve its biological meaning. The proposed model predicts soft biological brain ageing indicators with a six-class-balanced accuracy of . by using the anagraphic age of 1100 healthy subjects in comparison to their brain scans.作者: interlude 時間: 2025-3-22 19:34 作者: Mettle 時間: 2025-3-22 21:28 作者: SPURN 時間: 2025-3-23 05:13
,Summarizing Global SARS-CoV-2 Geographical Spread by?Phylogenetic Multitype Branching Models,ormation on the place of sampling of each strain. We find that even with such coarse–grained data the dominating transition rates exhibit weak similarities with the most popular, continent–level aggregated, airline passenger flight routes.作者: 音樂會 時間: 2025-3-23 05:51
0302-9743 d and selected from 26 submissions, and they focus on bioinformatics, computational biology, health informatics, cheminformatics, biotechnology, biostatistics, and biomedical imaging..978-3-031-20836-2978-3-031-20837-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: subordinate 時間: 2025-3-23 11:34
Physiologie der Appetitregulation,of their IC50 values, and we integrated it by linking cell lines to their respective tissue of origin and genomic profile. We performed two different kind of experiments: a) prediction of missing values in the matrix, b) prediction of the complete drug profile of a new cell line, demonstrating the validity of the method in both scenarios.作者: 無價值 時間: 2025-3-23 16:54 作者: 預知 時間: 2025-3-23 18:15 作者: gustation 時間: 2025-3-24 00:52
Biochemische Individualit?t und Gichtsent this new scenario, focusing on chemical mechanisms and systems that are topologically organized as neural networks, highlighting their possible role in synthetic cell biotechnology. Future directions, challenges and requirements, as well as epistemological interpretations are also briefly discussed.作者: Barter 時間: 2025-3-24 03:11
E?st?rungen: überblick aus klinischer Sicht of using sequence-derived features together with genomic context features for computational sRNA prediction and generated a new model sRNARanking v2 with increased predictive performance in terms of the area under the precision-recall curve (AUPRC). sRNARanking v2 is available at:..作者: limber 時間: 2025-3-24 07:22
P. Fürst,B. Josephson,E. Vinnarsdiagrams, which describe a series of molecular interactions leading to a certain biological function based on a set of rules and domain knowledge. Our method iteratively generates each pathway relationship uniquely. These realistic replicas improve the generalization significantly across a variety of settings. The code is available at ..作者: Exuberance 時間: 2025-3-24 12:15
Wichtige seltenere Stoffwechselkrankheiten,es as a crucial step for proper machine learning solutions development, validation, and data sharing. Such practices include detailing the data acquisition process, aiming for automatic integration of causal relationships and actionable metadata.作者: fringe 時間: 2025-3-24 16:21 作者: monopoly 時間: 2025-3-24 19:42
Improving Bacterial sRNA Identification By Combining Genomic Context and Sequence-Derived Features, of using sequence-derived features together with genomic context features for computational sRNA prediction and generated a new model sRNARanking v2 with increased predictive performance in terms of the area under the precision-recall curve (AUPRC). sRNARanking v2 is available at:..作者: Foregery 時間: 2025-3-25 01:06
A Rule-Based Approach for Generating Synthetic Biological Pathways,diagrams, which describe a series of molecular interactions leading to a certain biological function based on a set of rules and domain knowledge. Our method iteratively generates each pathway relationship uniquely. These realistic replicas improve the generalization significantly across a variety of settings. The code is available at ..作者: 整潔 時間: 2025-3-25 06:45
,The Need of?Standardised Metadata to?Encode Causal Relationships: Towards Safer Data-Driven Machinees as a crucial step for proper machine learning solutions development, validation, and data sharing. Such practices include detailing the data acquisition process, aiming for automatic integration of causal relationships and actionable metadata.作者: Mystic 時間: 2025-3-25 11:20 作者: 機密 時間: 2025-3-25 12:18
Development of Bayesian Network for Multiple Sclerosis Risk Factor Interaction Analysis, prediction, such as using machine learning and other statistical methods. However, many of these methods cannot properly capture complex relationships between variables that affect results of odds ratios unless independence between risk factors is assumed. This work addresses this limitation using 作者: 光亮 時間: 2025-3-25 17:33
Real-Time Automatic Plankton Detection, Tracking and Classification on Raw Hologram,s been used to detect and count various microscopic objects and has been applied in submersible equipment to monitor the . distribution of plankton. To count and classify plankton, conventional methods require a holographic reconstruction step to decode the hologram before identifying the objects. H作者: 野蠻 時間: 2025-3-25 21:26
The First , Model of Leg Movement Activity During Sleep, not showing significant periodic leg movements (PLM). To test a single generator hypothesis behind PLM—a single pacemaker possibly resulting from two (or more) interacting spinal/supraspinal generators—we added a periodic excitatory input to the control model. We describe the onset of a movement in作者: BRINK 時間: 2025-3-26 02:37
Transfer Learning and Magnetic Resonance Imaging Techniques for the Deep Neural Network-Based Diagnm scratch, transfer learning methods have allowed retraining deep networks, which were already trained on massive data repositories, using a smaller dataset from a new application domain, and have demonstrated high performance in several application areas. In the context of a diagnosis of neurodegen作者: 采納 時間: 2025-3-26 06:47
Improving Bacterial sRNA Identification By Combining Genomic Context and Sequence-Derived Features, The large diversity of sRNAs in terms of their length, sequence, and function poses a challenge for computational sRNA prediction. There are several bacterial sRNA prediction tools. Most of them use sequence-derived features or rely on phylogenetic conservation. Recently, a new sRNA predictor (sRNA作者: BARB 時間: 2025-3-26 08:45
High-Dimensional Multi-trait GWAS By Reverse Prediction of Genotypes Using Machine Learning Methodse correlated traits simultaneously, and have higher statistical power than independent univariate analyses of traits. Reverse regression, where genotypes of genetic variants are regressed on multiple traits simultaneously, has emerged as a promising approach to perform multi-trait GWAS in high-dimen作者: TAP 時間: 2025-3-26 16:28
,A Non-Negative Matrix Tri-Factorization Based Method for?Predicting Antitumor Drug Sensitivity,t of Non-Negative Matrix Tri-Factorization method, which allows the integration of different data types for the prediction of missing associations. To test our method we retrieved a dataset from the Cancer Cell Line Encyclopedia (CCLE), containing the connections among cell lines and drugs by means 作者: machination 時間: 2025-3-26 17:59
A Rule-Based Approach for Generating Synthetic Biological Pathways, However, applying deep learning models to a wider variety of domains is often limited by available labeled data. To address this problem, conventional approaches supplement more samples by augmenting existing datasets. However, these up-sampling methods usually only create derivations of the source作者: Demonstrate 時間: 2025-3-26 22:23
Machine Learning Classifiers Based on Dimensionality Reduction Techniques for the Early Diagnosis ogenerative diseases has recently shown a potential field of application for these methods. The performance comparison of a unique algorithm in various study contexts can be biased, which usually leads to incorrect results. In this context, this study consists in comparing the performance of differen作者: Salivary-Gland 時間: 2025-3-27 01:24 作者: 秘密會議 時間: 2025-3-27 06:24
,Sentence Classification to?Detect Tables for?Helping Extraction of?Regulatory Interactions in?Bacteto date by manual curation is rather than impossible. Despite the efforts in biomedical text mining, there are still challenges in extracting regulatory interactions (RIs) between transcription factors and genes from text documents. One of them is produced by text extraction from PDF files. We have 作者: labyrinth 時間: 2025-3-27 10:43
,RF-Isolation: A Novel Representation of?Structural Connectivity Networks for?Multiple Sclerosis Clag MR images, connectivity networks can be obtained. The analysis of structural connectivity networks of multiple sclerosis patients usually employs network-derived metrics, which are computed independently for each subject. We propose a novel representation of connectivity networks that is extracted作者: 噱頭 時間: 2025-3-27 17:12 作者: 貧窮地活 時間: 2025-3-27 19:08
,Explainable AI Models for?COVID-19 Diagnosis Using CT-Scan Images and?Clinical Data,ped decrease its number of deaths. Artificial Intelligence (AI) and Machine Learning (ML) techniques are a new era, where the main objective is no longer to assist experts in decision-making but to improve and increase their capabilities and this is where interpretability comes in. This study aims t作者: 缺陷 時間: 2025-3-27 22:53 作者: vitreous-humor 時間: 2025-3-28 02:38 作者: foodstuff 時間: 2025-3-28 08:09 作者: Ornithologist 時間: 2025-3-28 13:45 作者: gratify 時間: 2025-3-28 17:39
Computational Intelligence Methods for Bioinformatics and Biostatistics978-3-031-20837-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: FACET 時間: 2025-3-28 21:27
https://doi.org/10.1007/978-3-031-20837-9artificial intelligence; biostatistics; computational and systems biology; computer networks; computer s作者: Airtight 時間: 2025-3-29 01:16 作者: 思鄉(xiāng)病 時間: 2025-3-29 04:21 作者: 止痛藥 時間: 2025-3-29 10:35
Biochemische Individualit?t und Gicht can be used for modeling organisms’ features and behaviors. The recent Synthetic Biology advancements in the so-called “synthetic cells” area allow the construction of cell-like systems with non trivial complexity, paving the way to a novel direction: the realization of chemical artificial intellig作者: 招人嫉妒 時間: 2025-3-29 12:26
Biochemische Individualit?t und Gicht prediction, such as using machine learning and other statistical methods. However, many of these methods cannot properly capture complex relationships between variables that affect results of odds ratios unless independence between risk factors is assumed. This work addresses this limitation using 作者: 闡明 時間: 2025-3-29 15:36
E?st?rungen: überblick aus klinischer Sichts been used to detect and count various microscopic objects and has been applied in submersible equipment to monitor the . distribution of plankton. To count and classify plankton, conventional methods require a holographic reconstruction step to decode the hologram before identifying the objects. H作者: Aggrandize 時間: 2025-3-29 21:31 作者: Lament 時間: 2025-3-30 03:13 作者: synovium 時間: 2025-3-30 07:24
E?st?rungen: überblick aus klinischer Sicht The large diversity of sRNAs in terms of their length, sequence, and function poses a challenge for computational sRNA prediction. There are several bacterial sRNA prediction tools. Most of them use sequence-derived features or rely on phylogenetic conservation. Recently, a new sRNA predictor (sRNA作者: 細頸瓶 時間: 2025-3-30 10:54 作者: 蜿蜒而流 時間: 2025-3-30 16:03
Physiologie der Appetitregulation,t of Non-Negative Matrix Tri-Factorization method, which allows the integration of different data types for the prediction of missing associations. To test our method we retrieved a dataset from the Cancer Cell Line Encyclopedia (CCLE), containing the connections among cell lines and drugs by means 作者: 流逝 時間: 2025-3-30 19:48
P. Fürst,B. Josephson,E. Vinnars However, applying deep learning models to a wider variety of domains is often limited by available labeled data. To address this problem, conventional approaches supplement more samples by augmenting existing datasets. However, these up-sampling methods usually only create derivations of the source作者: hypotension 時間: 2025-3-30 22:28
Changes in Lipid Metabolism under Stress,generative diseases has recently shown a potential field of application for these methods. The performance comparison of a unique algorithm in various study contexts can be biased, which usually leads to incorrect results. In this context, this study consists in comparing the performance of differen作者: 交響樂 時間: 2025-3-31 02:43
https://doi.org/10.1007/978-3-662-30383-2biological papers. Each pathway figure encompasses rich biological information, consisting of gene names and gene relations. However, manual curations for pathway figures require tremendous time and labor. While leveraging advanced image understanding models may accelerate the process of curations, 作者: Pde5-Inhibitors 時間: 2025-3-31 05:42 作者: 侵略主義 時間: 2025-3-31 13:03
Immunbiologie des Kindesalters,g MR images, connectivity networks can be obtained. The analysis of structural connectivity networks of multiple sclerosis patients usually employs network-derived metrics, which are computed independently for each subject. We propose a novel representation of connectivity networks that is extracted作者: jovial 時間: 2025-3-31 15:28
Immunbiologie des Kindesalters,y interpretable parameters. To this end we fit a hidden state multistate speciation and extinction model to a pre-estimated phylogenetic tree with information on the place of sampling of each strain. We find that even with such coarse–grained data the dominating transition rates exhibit weak similar作者: Hiatus 時間: 2025-3-31 18:33
https://doi.org/10.1007/978-3-662-25013-6ped decrease its number of deaths. Artificial Intelligence (AI) and Machine Learning (ML) techniques are a new era, where the main objective is no longer to assist experts in decision-making but to improve and increase their capabilities and this is where interpretability comes in. This study aims t作者: 殘酷的地方 時間: 2025-3-31 22:50
Wichtige seltenere Stoffwechselkrankheiten, the robustness and generalisation capacity of the models, such as induced biases. This issue often arises when the algorithm decision is affected by confounding factors. In this work, we argue that the integration of research assumptions as causal relationships can help identify potential confounde作者: 知識分子 時間: 2025-4-1 04:29
Hans Josef Karl,Hans J?rg Bauerudy, the dataset of interest is that of coronaviruses. Coronaviridae are a family of positive-sense RNA viruses capable of infecting humans and animals. These viruses usually cause mild to moderate upper respiratory tract infection; however, they can also cause more severe symptoms, gastrointestinal作者: Phonophobia 時間: 2025-4-1 06:02
Stoffwechsel Ern?hrung Endokrinium arise. From the computational and mathematical perspective, we have to deal with a dataset with ultra-high volume and ultra-high dimensionality in several experimental studies. An indicative example is DNA sequencing technologies, which offer a more realistic picture of human diseases at the molecu
