scholarly journals Automatic Gene Function Prediction in the 2020’s

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1264
Author(s):  
Stavros Makrodimitris ◽  
Roeland C. H. J. van Ham ◽  
Marcel J. T. Reinders
Keyword(s):  
Functional Annotation ◽  
Protein Sequences ◽  
Research Area ◽  
Function Prediction ◽  
Research Field ◽  
Model Species ◽  
Large Step ◽  
Gene Functions ◽  
Performance Gains ◽  
The Way

The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, emphasizing the need for accurate Automatic Function Prediction (AFP) methods. AFP has been an active and growing research field for decades and has made considerable progress in that time. However, it is certainly not solved. In this paper, we describe challenges that the AFP field still has to overcome in the future to increase its applicability. The challenges we consider are how to: (1) include condition-specific functional annotation, (2) predict functions for non-model species, (3) include new informative data sources, (4) deal with the biases of Gene Ontology (GO) annotations, and (5) maximally exploit the GO to obtain performance gains. We also provide recommendations for addressing those challenges, by adapting (1) the way we represent proteins and genes, (2) the way we represent gene functions, and (3) the algorithms that perform the prediction from gene to function. Together, we show that AFP is still a vibrant research area that can benefit from continuing advances in machine learning with which AFP in the 2020s can again take a large step forward reinforcing the power of computational biology.

scholarly journals IsoResolve: predicting splice isoform functions by integrating gene and isoform-level features with domain adaptation

2020 ◽  
Author(s):  
Hong-Dong Li ◽  
Changhuo Yang ◽  
Zhimin Zhang ◽  
Mengyun Yang ◽  
Fang-Xiang Wu ◽  
...  
Keyword(s):  
Latent Variables ◽  
Functional Annotation ◽  
Latent Variable ◽  
Prediction Models ◽  
Domain Adaptation ◽  
Single Gene ◽  
Function Prediction ◽  
Supplementary Information ◽  
Similar Distribution ◽  
Gene Functions

Abstract Motivation High resolution annotation of gene functions is a central goal in functional genomics. A single gene may produce multiple isoforms with different functions through alternative splicing. Conventional approaches, however, consider a gene as a single entity without differentiating these functionally different isoforms. Towards understanding gene functions at higher resolution, recent efforts have focused on predicting the functions of isoforms. However, the performance of existing methods is far from satisfactory mainly because of the lack of isoform-level functional annotation. Results We present IsoResolve, a novel approach for isoform function prediction, which leverages the information from gene function prediction models with domain adaptation (DA). IsoResolve treats gene-level and isoform-level features as source and target domains, respectively. It uses DA to project the two domains into a latent variable space in such a way that the latent variables from the two domains have similar distribution, which enables the gene domain information to be leveraged for isoform function prediction. We systematically evaluated the performance of IsoResolve in predicting functions. Compared with five state-of-the-art methods, IsoResolve achieved significantly better performance. IsoResolve was further validated by case studies of genes with isoform-level functional annotation. Availability and implementation IsoResolve is freely available at https://github.com/genemine/IsoResolve. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Diketopyrrolopyrrole Fluorescent Probes, Photophysical and Biological Applications

Chemosensors ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 44
Author(s):  
Muhammad Aminu Auwalu ◽  
Shanshan Cheng
Keyword(s):  
Quantum Yield ◽  
Fluorescent Probes ◽  
Organic Dyes ◽  
Tumor Therapy ◽  
Research Area ◽  
Research Field ◽  
Review Article ◽  
Biological Applications ◽  
Chemistry Research ◽  
Cancer Tumor

Biological applications of fluorescent probes are rapidly increasing in the supramolecular chemistry research field. Several organic dyes are being utilized currently in developing and advancing this attractive research area, of which diketopyrrolopyrrole (DPP) organic dyes show an exceptional photophysical features (high-fluorescence quantum yield (FQY), good photochemical and thermal stability) that are essential properties for biological applications. Great efforts have been made in recent years towards developing novel fluorescent DPPs by different chemists for such applications, and some positive results have been reported. As a result, this review article gives an account of the progress that has so far been made very recently, mainly within the last decade, in that we selectively focus on and discuss more from 2015 to present on some recent scholarly achievements of fluorescent DPPs: quantum yield, aggregation-induced emission (AIE), solid-state emission, bio-imaging, cancer/tumor therapy, mitochondria staining and some polymeric fluorescent DPPs. Finally, this review article highlights researchers working on luminescent DPPs and the future prospects in some key areas towards designing DPP-based fluorescent probes in order to boost their photophysical and biological applications more effectively.

scholarly journals SubFeat: Feature Subspacing Ensemble Classifier for Function Prediction of DNA, RNA and Protein Sequences

2021 ◽  
pp. 107489
Author(s):  
H.M.Fazlul Haque ◽  
Muhammod Rafsanjani ◽  
Fariha Arifin ◽  
Sheikh Adilina ◽  
Swakkhar Shatabda
Keyword(s):  
Protein Sequences ◽  
Ensemble Classifier ◽  
Function Prediction

scholarly journals Usability Methods and Attributes Reported in Usability Studies of Mobile Apps for Health Care Education: Protocol for a Scoping Review

10.2196/19072 ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. e19072
Author(s):  
Susanne Grødem Johnson ◽  
Thomas Potrebny ◽  
Lillebeth Larun ◽  
Donna Ciliska ◽  
Nina Rydland Olsen
Keyword(s):  
Health Care ◽  
Scoping Review ◽  
Mobile Apps ◽  
Research Question ◽  
Grey Literature ◽  
Research Area ◽  
Research Field ◽  
Learning Technologies ◽  
Health Care Education ◽  
Care Education

Background E-learning technologies, including mobile apps, are used to a large extent in health care education. Mobile apps can provide extendable learning environments and motivate students for adaptive and collaborative learning outside the classroom context. Developers should design practical, effective, and easy-to-use mobile apps. Usability testing is an important part of app development in order to understand if apps meet the needs of users. Objective The aim of this study is to perform a scoping review of usability methods and attributes reported in usability studies of mobile apps for health care education. Methods The scoping review is guided by the methodological framework developed by Arksey & O’Malley and further developed by Levac et al and Kahlil et al. The stages we will follow are as follows: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies; (4) charting the data; and (5) summarizing and reporting the results. We have developed two research questions to meet the aim of the study, which are as follows: (1) What usability methods are used to evaluate the usability of mobile apps for health care education? and (2) What usability attributes are reported in the usability studies of mobile apps for health care education? We will apply a comprehensive search of the literature, including 10 databases, a reference search, and a search for grey literature. Two review authors will independently screen articles for eligibility. Results The initial electronic database searches were completed in March 2019. The literature search identified 14,297 unique references. Following title and abstract screening, the full texts of 369 records were obtained. The scoping review is expected to be completed in spring 2021. Conclusions We expect the overview of usability methods and attributes reported in usability studies of mobile apps for health care education to contribute to the knowledge base for researchers and developers. It will give an overview of the research field and provide researchers and developers with relevant and important information on the usability research area, including highlighting possible research gaps. International Registered Report Identifier (IRRID) DERR1-10.2196/19072

Lifelog and Information Retrieval from Daily Digital Data: Narrative Review. (Preprint)

2021 ◽  
Author(s):  
Ricardo Ribeiro ◽  
Alina Trifan ◽  
António J. R. Neves
Keyword(s):  
Contextual Information ◽  
Life Quality ◽  
Research Area ◽  
Research Field ◽  
Narrative Review ◽  
Digital Data ◽  
Significant Information ◽  
Memory Problems ◽  
Wide Availability ◽  
And Behaviors

BACKGROUND The wide availability and small size, together with the decrease in pricing of different types of sensors, has made it possible, over the last decade, to acquire a huge amount of data about a person's life in real time. These sensors can be incorporated into personal electronic devices available at reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity and physiological signals, among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. OBJECTIVE The goal of this article is to review the literature in the research area of lifelogging over the past decade and provide an historical overview on this research topic. To this purpose, we analyze lifelogging applications that monitor and assist people with memory problems. METHODS We follow a narrative review methodology to conduct a comprehensive search of relevant publications in Google Scholar and Scopus databases. In order to find these relevant publication, topic-related keywords were identified and combined based on different lifelogging type of data and applications. RESULTS A total of 124 publications were selected and included in this narrative review. 411 publications were retrieved and screened from the two scholar databases. Out of these, 114 publications were fully reviewed. In addition, 32 more publications were manually included based on our bibliographical knowledge in this research field. CONCLUSIONS The use of personal lifelogs can be beneficial to improve the life quality of people suffering from memory problems, such as dementia. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories to be used as surrogate memory. Through this narrative we understand that contextual information can be extracted from the lifelogs and it provides significant information for understanding the daily life of people suffering from memory issues based on events, experiences and behaviors.

ON THE TAXONOMY OF COURTROOM NARRATIVES

2021 ◽  
pp. 122-127
Author(s):  
O.A. Boginskaya ◽  
Keyword(s):  
Research Field ◽  
Classification Criteria ◽  
Propositional Content ◽  
Narrative Construction ◽  
Narrative Structures ◽  
The Status ◽  
Chronological Sequence ◽  
Crime Event ◽  
The Way

The study is based on the assumption about the narrative nature of courtroom discourse and aims at analyzing the structure and varieties of courtroom narrative. Courtroom narrative is defined as a way of organizing courtroom discourse whose propositional content is a story with crime event elements included in this story in their chronological sequence that correlate with reality and the speaker’s experience. Four classification criteria for courtroom narrative practices are proposed: 1) the degree of completeness; 2) the ways of description; 3) the type of determinants; 4) the way of reality representation. By the degree of completeness, there are complete and truncated narratives; by the way of description - neutral and evaluative; by the type of determinant - phenomenological and professional; by the way of representing reality - narrative construction and narrative reflection. The article concludes that the study of courtroom narrative is a promising research field, since there are avenues for researchers such as the status of interpretive schemes in the narrative, narrative structures in different legal cultures, the ratio of narrative and recontextualization.

Towards Personal, Social, and Urban Awareness

2014 ◽  
pp. 1-20 ◽  
Author(s):  
Bin Guo ◽  
Yunji Liang ◽  
Zhu Wang ◽  
Zhiwen Yu ◽  
Daqing Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
General System ◽  
Group Behavior ◽  
Research Area ◽  
Research Field ◽  
Urban Context ◽  
Urban Dynamics ◽  
Context Aware Computing ◽  
Social And Community Intelligence ◽  
New Research

In the past decades, numerous research efforts have been made to model and extract the contexts of users in pervasive computing environments. The recent explosion of sensor-equipped mobile phone market and the phenomenal growth of geo-tagged data (Twitter messages, Foursquare check-ins, etc.) have enabled the analysis of new dimensions of contexts that involve the social and urban context. The technology trend towards pervasive sensing and large-scale social and community computing is making “Social and Community Intelligence (SCI)” a new research area that aims at investigating individual/group behavior patterns, community and urban dynamics based on the “digital footprints.” It is believed that the SCI technology has the potential to revolutionize the field of context-aware computing. The aim of this chapter is to identify this emerging research area, present the research background, define the general system framework, characterize its unique properties, discuss the open research challenges, and present this emerging research field.

Information Retrieval Technologies and the “Realities” of Music Information Seeking

2016 ◽  
pp. 102-121
Author(s):  
Charilaos Lavranos ◽  
Petros Kostagiolas ◽  
Joseph Papadatos
Keyword(s):  
Information Retrieval ◽  
Information Seeking ◽  
Research Area ◽  
Music Technology ◽  
Information Seeking Behavior ◽  
Seeking Behavior ◽  
Evolution Of Music ◽  
Music Information ◽  
Search And Retrieval ◽  
The Way

Music information seeking incorporates the human activities that are carried out for the search and retrieval of music information. In recent years, the evolution of music technology holds a central role affecting the nature of music information seeking behavior. The research area that deals with the accessibility and the retrievability process of music information is known as Music Information Retrieval (MIR). This chapter focuses on the presentation of MIR technologies which has a direct impact in the way that individuals, as well as different music communities such as composers, performers, listeners, musicologists, etc., handle and utilize music information. The aim of this chapter is to investigate the way different music communities interact with MIR systems. Our approach is based on a selected literature review regarding the MIR systems and the information seeking behavior of the musicians.

A Primer on Text-Data Analysis

2011 ◽  
pp. 3111-3118 ◽  
Author(s):  
Imad Rahal ◽  
Baoying Wang ◽  
James Schnepf
Keyword(s):  
Information Retrieval ◽  
Data Analysis ◽  
Language Processing ◽  
Information Filtering ◽  
Data Representation ◽  
Research Area ◽  
Research Field ◽  
Text Data ◽  
Document Collections ◽  
Text Data Analysis

Since the invention of the printing press, text has been the predominate mode for collecting, storing and disseminating a vast, rich range of information. With the unprecedented increase of electronic storage and dissemination, document collections have grown rapidly, increasing the need to manage and analyze this form of data in spite of its unstructured or semistructured form. Text-data analysis (Hearst, 1999) has emerged as an interdisciplinary research area forming a junction of a number of older fields like machine learning, natural language processing, and information retrieval (Grobelnik, Mladenic, & Milic-Frayling, 2000). It is sometimes viewed as an adapted form of a very similar research field that has also emerged recently, namely, data mining, which focuses primarily on structured data mostly represented in relational tables or multidimensional cubes. This article provides an overview of the various research directions in text-data analysis. After the “Introduction,” the “Background” section provides a description of a ubiquitous text-data representation model along with preprocessing steps employed for achieving better text-data representations and applications. The focal section, “Text-Data Analysis,” presents a detailed treatment of various text-data analysis subprocesses such as information extraction, information retrieval and information filtering, document clustering and document categorization. The article closes with a “Future Trends” section followed by a “Conclusion” section.

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