Limit your search
Search Constraints
« Previous |
1 - 10 of 13
|
Next »
Number of results to display per page
Search Results
-
- Description:
- Cite this article: Shen, J., McFarland, A.G., Blaustein, R.A. et al. An improved workflow for accurate and robust healthcare environmental surveillance using metagenomics. Microbiome 10, 206 (2022). https://doi.org/10.1186/s40168-022-01412-x and Background: Effective surveillance of microbial communities in the healthcare environment is increasingly important in infection prevention. Metagenomics-based techniques are promising due to their untargeted nature but are currently challenged by several limitations: (1) they are not powerful enough to extract valid signals out of the background noise for low-biomass samples,...
- Keyword:
- Environmental surveillance, Low biomass, Sequencing depth prediction, Infection prevention, Machine learning, Quantitative metagenomics, Viability, and Quantification
- Subject:
- Environmental monitoring, Nosocomial infections--Prevention, Quantitative research, Machine learning, and Metagenomics
- Creator:
- K. Allison Perry-Dow, Anahid A. Moghadam, Vincent B. Young, Alexander G. McFarland, Laura J. Rose, Ryan A. Blaustein, Erica M. Hartmann , Jiaxian Shen, and Mary K. Hayden
- Contributor:
- Centers for Disease Control and Prevention (funding agency)
- Owner:
- Jiaxian SHEN
- Publisher:
- Microbiome
- Language:
- English
- Date Uploaded:
- 12/19/2022
- Date Modified:
- 12/19/2022
- Date Created:
- 2022-12-02
- Resource Type:
- Research Paper
- Alternate Identifier:
- DOI 10.1186/s40168-022-01412-x, PMID 36457108, and PMCID PMC9716758
-
- Description:
- Engineering design is a systematic process of identifying needs and their translation into functional systems. This is a cyclic process that alternates between the acquisition of data and the synthesis of said data to inform design decisions. Conventionally, data from physical experiments are used to explore the efficacy of alternative...
- Keyword:
- Uncertainty quantification, Machine learning, Design, Data acquisition, Decision making, and Data synthesis
- Subject:
- Design and Mechanical engineering
- Creator:
- van Beek, Anton
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/02/2022
- Date Created:
- 2021-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_861337 and http://dissertations.umi.com/northwestern:15848
-
- Description:
- Metal–organic frameworks (MOFs) are a class of crystalline materials composed of metal nodes connected by organic linkers. Due to their high degree of synthetic tunability, MOFs have been considered for a wide range of applications, including many that rely on a change in oxidation state. While most MOFs are generally...
- Keyword:
- Metal-organic framework, Machine learning, Density functional theory, and Computational screening
- Subject:
- Chemical engineering
- Creator:
- Rosen, Andrew Scott
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 10/07/2021
- Date Created:
- 2021-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15675 and etdadmin_upload_838355
-
- Description:
- In the short amount of time that genetic manipulation has been possible through CRISPR technology, myriad applications have been developed. Results from one of the most promising applications of this technology, pooled screens, have shown that single guide RNAs (sgRNAs), RNA sequences used to target specific regions of the genome,...
- Keyword:
- sgRNA design, Machine learning, and CRISPR efficiency
- Subject:
- Biostatistics, Bioinformatics, and Statistics
- Creator:
- Zarate, Oscar Alberto
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_773909 and http://dissertations.umi.com/northwestern:15353
-
- Description:
- Sound is one of the most important mediums to understand the environment around us. Identifying a sound event in prerecorded audio (such as a police siren, a dog bark, or a creaking door in soundscapes) leads to a better understanding of the context where the sound events occurred. To do...
- Keyword:
- Sound event detection, Machine learning, Human-in-the-loop interface, Sound event annotation, and Audio signal processing
- Subject:
- Computer science and Artificial intelligence
- Creator:
- Kim, Bongjun
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 01/21/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15064 and etdadmin_upload_739320
-
- Description:
- In machine learning, classification that assigns a label to a sample is a fundamental problem and serves a building block for various applications of artificial intelligence such as speech recognition, sentimental analysis, and image recognition. During the last years, deep learning rejuvenates artificial intelligence; in particular, it leads to tremendous...
- Keyword:
- Machine learning, Classification, and Deep learning
- Subject:
- Industrial engineering
- Creator:
- Koo, Jaehoon
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 01/21/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_729998 and http://dissertations.umi.com/northwestern:15036
-
- Description:
- Functional electronic materials are difficult to design due to the complex interplay among chemistry, atomic structure, and electrical properties. This dilemma is further amplified in transition metal compounds which can defy the band-theory description of non-correlated electrons. Exploring the vast possible design space completely with experiments or first-principles simulations is...
- Keyword:
- Transition metal oxides, Machine learning, Metal-insulator transition, and Data science
- Subject:
- Materials Science
- Creator:
- Wagner, Nicholas Adam
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/12/2020
- Date Created:
- 2019-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:14800 and etdadmin_upload_685025
-
- Description:
- Biology is entering the exciting world of big data. Modern high-throughput experimental techniques often produce large datasets that aim to capture complex relationships often found in biological systems. While these larger data sets contain vast amounts of useful information, the answers are often locked behind a wall of numbers. As...
- Keyword:
- Machine learning and Data science
- Subject:
- Chemical and Biological Engineering
- Creator:
- Albert Xue
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 10/28/2019
- Date Modified:
- 10/28/2019
- Date Created:
- 2018-01-01
- Resource Type:
- Dissertation
-
- Description:
- Unstructured data like text is plentiful and possibly contains valuable insights leading to a better decision-making process. Manually obtaining these insights can be costly and time-consuming. Text mining, also known as Text analytics, is developed to derive meaningful information from textual data. It is widely applied in various domains such...
- Keyword:
- Machine learning, Text mining, Information retrieval, Document classification, and Text analytics
- Subject:
- Industrial Engineering and Management Sciences
- Creator:
- Papis Wongchaisuwat
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 02/22/2019
- Date Modified:
- 02/22/2019
- Date Created:
- 2018-01-01
- Resource Type:
- Dissertation
-
- Description:
- This dissertation uses several interrelated methods derived from corpus linguistics, statistics, and machine learning to infer a number of historically significant voice-leading schemas in a corpus of eighteenth-century Neapolitan solfeggi (exercises for voice with bass accompaniment). The goal of this work is to gain insights not only into the characteristics...
- Keyword:
- Schema theory, Temporal regularity, Machine learning, Galant style, Music cognition, and Structure mapping theory
- Subject:
- Music
- Creator:
- James Symons
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 01/16/2019
- Date Modified:
- 01/16/2019
- Date Created:
- 2017-01-01
- Resource Type:
- Dissertation