標(biāo)題: Titlebook: Algorithms for Computational Biology; 7th International Co Carlos Martín-Vide,Miguel A. Vega-Rodríguez,Travis Conference proceedings 2020 S [打印本頁(yè)] 作者: charity 時(shí)間: 2025-3-21 17:31
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作者: 矛盾心理 時(shí)間: 2025-3-21 21:46 作者: EVEN 時(shí)間: 2025-3-22 01:35 作者: 就職 時(shí)間: 2025-3-22 04:45 作者: 合群 時(shí)間: 2025-3-22 12:03
Gaps and Runs in Syntenic Alignmentstural roles, compensating for the energy and material costs of gene complement expansion..A type of gene loss widespread in the lineages of plant genomes is “fractionation” after whole genome doubling or tripling, where one of a pair or triplet of paralogous genes in parallel syntenic contexts is di作者: 溺愛(ài) 時(shí)間: 2025-3-22 16:29
Comparing Integer Linear Programming to SAT-Solving for Hard Problems in Computational and Systems Br, intricate algorithms for each specific problem. Integer Linear Programming is the most widely-used such general-purpose solution method. It is successful in a wide range of problems. However, there are some problems in computational biology where integer linear programming has had only limited su作者: badinage 時(shí)間: 2025-3-22 17:59
Combining Networks Using Cherry Picking Sequencesnly reconstruct small networks. To find bigger networks, one can attempt to combine small networks. In this paper, we study the . problem, a problem of combining networks into another network with low complexity. We characterize this complexity via a restricted problem, ., and we present an FPT algo作者: 土坯 時(shí)間: 2025-3-22 22:44 作者: 豐富 時(shí)間: 2025-3-23 03:44
PathOGiST: A Novel Method for Clustering Pathogen Isolates by Combining Multiple Genotyping Signalsng methods for this problem mainly use a single genotyping signal, and either use a distance-based method with a pre-specified number of clusters, or a phylogenetic tree-based method with a pre-specified threshold. We propose PathOGiST, an algorithmic framework for clustering bacterial isolates by l作者: fatty-streak 時(shí)間: 2025-3-23 08:05 作者: Resection 時(shí)間: 2025-3-23 09:45 作者: Aqueous-Humor 時(shí)間: 2025-3-23 14:15
BESTox: A Convolutional Neural Network Regression Model Based on Binary-Encoded SMILES for Acute Oraiments are required to confirm the acute oral toxicity of chemical compounds. However, these methods are often restricted by availability of experimental facilities, long experimentation time, and high cost. In this paper, we propose a novel convolutional neural network regression model, named BESTo作者: 紡織品 時(shí)間: 2025-3-23 20:54
Stratified Test Alleviates Batch Effects in Single-Cell Data, elegantly mitigates the problem. We also modified the common language effect size to supplement this test, further improving its utility. On both simulated and real patient data we show the ability of Van Elteren test to control for false positives and false negatives. The effect size also estimat作者: Heretical 時(shí)間: 2025-3-23 22:45
A Topological Data Analysis Approach on?Predicting Phenotypes from Gene Expression Dataividuals in the context of phenotype prediction. We observed that standard machine learning methods alone performed somewhat poorly on the disease phenotype prediction task; therefore we devised an approach augmenting machine learning with topological data analysis..We describe a framework for predi作者: occult 時(shí)間: 2025-3-24 04:00 作者: 去掉 時(shí)間: 2025-3-24 09:47 作者: 僵硬 時(shí)間: 2025-3-24 11:38 作者: Acetaldehyde 時(shí)間: 2025-3-24 18:04
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/153208.jpg作者: 領(lǐng)先 時(shí)間: 2025-3-24 22:54
https://doi.org/10.1007/978-3-030-42266-0artificial intelligence; bioinformatics; communication; computational genomics; computer networks; correl作者: 字的誤用 時(shí)間: 2025-3-25 01:54
978-3-030-42265-3Springer Nature Switzerland AG 2020作者: 元音 時(shí)間: 2025-3-25 04:14
Produktionsdaten im Stolba-Familienstall,l-being. However, such datasets are large in volume, and retrieving meaningful information from them is often challenging. Hence, different indexing techniques and data structures have been proposed to handle such a massive scale of data. We utilize one such technique: Generalized Suffix Tree (GST).作者: indenture 時(shí)間: 2025-3-25 07:55 作者: Engaging 時(shí)間: 2025-3-25 12:48 作者: Volatile-Oils 時(shí)間: 2025-3-25 16:18 作者: 咯咯笑 時(shí)間: 2025-3-25 22:16 作者: 半身雕像 時(shí)間: 2025-3-26 00:50 作者: 招募 時(shí)間: 2025-3-26 06:37 作者: 一窩小鳥(niǎo) 時(shí)間: 2025-3-26 12:18 作者: Pander 時(shí)間: 2025-3-26 12:40
https://doi.org/10.1007/978-3-8349-6980-4ng methods for this problem mainly use a single genotyping signal, and either use a distance-based method with a pre-specified number of clusters, or a phylogenetic tree-based method with a pre-specified threshold. We propose PathOGiST, an algorithmic framework for clustering bacterial isolates by l作者: 遷移 時(shí)間: 2025-3-26 18:17 作者: 打算 時(shí)間: 2025-3-27 00:22 作者: 易受刺激 時(shí)間: 2025-3-27 03:27
https://doi.org/10.1007/978-3-658-03031-5iments are required to confirm the acute oral toxicity of chemical compounds. However, these methods are often restricted by availability of experimental facilities, long experimentation time, and high cost. In this paper, we propose a novel convolutional neural network regression model, named BESTo作者: 小步走路 時(shí)間: 2025-3-27 05:18
https://doi.org/10.1007/978-3-658-03031-5, elegantly mitigates the problem. We also modified the common language effect size to supplement this test, further improving its utility. On both simulated and real patient data we show the ability of Van Elteren test to control for false positives and false negatives. The effect size also estimat作者: COWER 時(shí)間: 2025-3-27 13:00 作者: extinct 時(shí)間: 2025-3-27 15:31
https://doi.org/10.1007/978-3-658-03031-5e original RNA transcripts from those fragments (RNA-Seq assembly) is still a difficult task. For example, RNA-Seq assembly tools typically require hyper-parameter tuning to achieve good performance for particular datasets. This kind of tuning is usually unintuitive and time-consuming. Consequently,作者: Badger 時(shí)間: 2025-3-27 20:20
https://doi.org/10.1007/978-3-658-33799-5 mathematically characterize s simple model in some detail and show how it is an adequate description neither of the . subgenomes nor its two progenitor genomes..We find that a mixture of two models, a random, one-gene-at-a-time, model and a geometric-length distributed excision for removing a variable number of genes, fits well.作者: heirloom 時(shí)間: 2025-3-28 01:50 作者: FADE 時(shí)間: 2025-3-28 04:40 作者: Foam-Cells 時(shí)間: 2025-3-28 07:55 作者: 1FAWN 時(shí)間: 2025-3-28 11:12
A Topological Data Analysis Approach on?Predicting Phenotypes from Gene Expression Datan when measured against standard machine learning methods..This study confirms that gene expression can be a useful indicator of the presence or absence of a condition, and the subtle signal contained in this high dimensional data reveals itself when considering the intricate topological connections between expressed genes.作者: macabre 時(shí)間: 2025-3-28 15:49
BOAssembler: A Bayesian Optimization Framework to Improve RNA-Seq Assembly Performancepproach is effective to improve the overall assembly performance. The approach would be helpful for downstream (e.g. gene, protein, cell) analysis, and more broadly, for future bioinformatics benchmark studies.. ..作者: HAVOC 時(shí)間: 2025-3-28 20:00 作者: 膽小鬼 時(shí)間: 2025-3-29 00:52
https://doi.org/10.1007/978-3-658-33799-5rved haplotype blocks to pangenomes, which can store more complex variation than a single reference genome. We define a . and give a linear-time, suffix tree based approach to find all such blocks from a set of pangenome haplotypes. We demonstrate the method by applying it to a pangenome built from yeast strains.作者: hegemony 時(shí)間: 2025-3-29 05:57
https://doi.org/10.1007/978-3-658-33799-5f combining networks into another network with low complexity. We characterize this complexity via a restricted problem, ., and we present an FPT algorithm to efficiently solve this restricted problem.作者: INERT 時(shí)間: 2025-3-29 09:58
https://doi.org/10.1007/978-3-8349-6980-4 on likelihoods of directed acyclic graphs. This algorithm is applied to transcript abundance data collected from . genes. This study extends the underlying statistical and mathematical theory of the Norris-Patton likelihood by including time series adjustments.作者: 油膏 時(shí)間: 2025-3-29 11:54 作者: 嚴(yán)厲批評(píng) 時(shí)間: 2025-3-29 17:43 作者: Impugn 時(shí)間: 2025-3-29 20:40 作者: 令人心醉 時(shí)間: 2025-3-30 00:00
Time Series Adjustment Enhancement of Hierarchical Modeling of , Gene Interactions on likelihoods of directed acyclic graphs. This algorithm is applied to transcript abundance data collected from . genes. This study extends the underlying statistical and mathematical theory of the Norris-Patton likelihood by including time series adjustments.作者: 嚙齒動(dòng)物 時(shí)間: 2025-3-30 04:45 作者: Crayon 時(shí)間: 2025-3-30 09:51
https://doi.org/10.1007/978-3-658-33799-5 the distance estimation in realistic data. In this work, we study the transposition distance between two genomes, but we also consider intergenic regions, a problem we name Sorting Permutations by Intergenic Transpositions (SbIT). We show that this problem is NP-hard and propose a 3.5-approximation algorithm for it.作者: Spinal-Tap 時(shí)間: 2025-3-30 15:14
https://doi.org/10.1007/978-3-8349-6980-4idual signals with correlation clustering, and combines the clusterings based on the individual signals through consensus clustering. We implemented and tested PathOGiST on three different bacterial pathogens - ., ., and . - and we conclude by discussing further avenues to explore.作者: chronology 時(shí)間: 2025-3-30 17:28 作者: 否決 時(shí)間: 2025-3-30 23:04 作者: 凈禮 時(shí)間: 2025-3-31 03:29
0302-9743 papers included in this volume were carefully reviewed and selected from 24 submissions. They were organized in topical sections on genomics, phylogenetics, and RNA-Seq and other biological processes.?.978-3-030-42265-3978-3-030-42266-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
