scholarly journals TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for High-Accuracy Gene Function Annotations

2021 ◽  
Author(s):  
Yi-Heng Zhu ◽  
Chengxin Zhang ◽  
Yan Liu ◽  
Gilbert S Omenn ◽  
Peter L Freddolino ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
Expression Profiles ◽  
Feature Space ◽  
Mapping Technique ◽  
Large Set ◽  
Transcript Expression ◽  
Function Annotation ◽  
Protein Coding ◽  
Go Annotation ◽  
Current State

Gene Ontology (GO) has been widely used to annotate functions of genes and gene products. We proposed a new method (TripletGO) to deduce GO terms of protein-coding and non-coding genes, through the integration of four complementary pipelines built on transcript expression profiling, genetic sequence alignment, protein sequence alignment and naive probability, respectively. TripletGO was tested on a large set of 5,754 genes from 8 species (human, mouse, arabidopsis, rat, fly, budding yeast, fission yeast, and nematoda) and 2,433 proteins with available expression data from the CAFA3 experiment and achieved function annotation accuracy significantly beyond the current state-of-the-art approaches. Detailed analyses show that the major advantage of TripletGO lies in the coupling of a new triplet-network based profiling method with the feature space mapping technique which can accurately recognize function patterns from transcript expressions. Meanwhile, the combination of multiple complementary models, especially those from transcript expression and protein-level alignments, improves the coverage and accuracy of the final GO annotation results. The standalone package and an online server of TripletGO are freely available at https://zhanglab.ccmb.med.umich.edu/TripletGO/.

scholarly journals Extending Geodemographics Using Data Primitives: A Review and a Methodological Proposal

2021 ◽  
Vol 10 (6) ◽  
pp. 386
Author(s):  
Jennie Gray ◽  
Lisa Buckner ◽  
Alexis Comber
Keyword(s):  
Social Dynamics ◽  
Feature Space ◽  
Social Processes ◽  
Multiple Time ◽  
Current State ◽  
Cluster Label ◽  
Static Data ◽  
The Social ◽  
Using Data

This paper reviews geodemographic classifications and developments in contemporary classifications. It develops a critique of current approaches and identifiea a number of key limitations. These include the problems associated with the geodemographic cluster label (few cluster members are typical or have the same properties as the cluster centre) and the failure of the static label to describe anything about the underlying neighbourhood processes and dynamics. To address these limitations, this paper proposed a data primitives approach. Data primitives are the fundamental dimensions or measurements that capture the processes of interest. They can be used to describe the current state of an area in a multivariate feature space, and states can be compared over multiple time periods for which data are available, through for example a change vector approach. In this way, emergent social processes, which may be too weak to result in a change in a cluster label, but are nonetheless important signals, can be captured. As states are updated (for example, as new data become available), inferences about different social processes can be made, as well as classification updates if required. State changes can also be used to determine neighbourhood trajectories and to predict or infer future states. A list of data primitives was suggested from a review of the mechanisms driving a number of neighbourhood-level social processes, with the aim of improving the wider understanding of the interaction of complex neighbourhood processes and their effects. A small case study was provided to illustrate the approach. In this way, the methods outlined in this paper suggest a more nuanced approach to geodemographic research, away from a focus on classifications and static data, towards approaches that capture the social dynamics experienced by neighbourhoods.

scholarly journals Ensemble-Based Out-of-Distribution Detection

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 567
Author(s):  
Donghun Yang ◽  
Kien Mai Mai Ngoc ◽  
Iksoo Shin ◽  
Kyong-Ha Lee ◽  
Myunggwon Hwang
Keyword(s):  
Detection Method ◽  
State Of The Art ◽  
Metric Learning ◽  
Feature Space ◽  
Confidence Score ◽  
Distance Metric Learning ◽  
Current State ◽  
Overall Performance ◽  
Deep Learning Model

To design an efficient deep learning model that can be used in the real-world, it is important to detect out-of-distribution (OOD) data well. Various studies have been conducted to solve the OOD problem. The current state-of-the-art approach uses a confidence score based on the Mahalanobis distance in a feature space. Although it outperformed the previous approaches, the results were sensitive to the quality of the trained model and the dataset complexity. Herein, we propose a novel OOD detection method that can train more efficient feature space for OOD detection. The proposed method uses an ensemble of the features trained using the softmax-based classifier and the network based on distance metric learning (DML). Through the complementary interaction of these two networks, the trained feature space has a more clumped distribution and can fit well on the Gaussian distribution by class. Therefore, OOD data can be efficiently detected by setting a threshold in the trained feature space. To evaluate the proposed method, we applied our method to various combinations of image datasets. The results show that the overall performance of the proposed approach is superior to those of other methods, including the state-of-the-art approach, on any combination of datasets.

scholarly journals Experiments of Image Classification Using Dissimilarity Spaces Built with Siamese Networks

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1573
Author(s):  
Loris Nanni ◽  
Giovanni Minchio ◽  
Sheryl Brahnam ◽  
Gianluca Maguolo ◽  
Alessandra Lumini
Keyword(s):  
Vector Space ◽  
Image Classification ◽  
Ad Hoc ◽  
Feature Space ◽  
Medical Data ◽  
Training Data ◽  
Data Sets ◽  
Large Set ◽  
Clustering Methods ◽  
Siamese Networks

Traditionally, classifiers are trained to predict patterns within a feature space. The image classification system presented here trains classifiers to predict patterns within a vector space by combining the dissimilarity spaces generated by a large set of Siamese Neural Networks (SNNs). A set of centroids from the patterns in the training data sets is calculated with supervised k-means clustering. The centroids are used to generate the dissimilarity space via the Siamese networks. The vector space descriptors are extracted by projecting patterns onto the similarity spaces, and SVMs classify an image by its dissimilarity vector. The versatility of the proposed approach in image classification is demonstrated by evaluating the system on different types of images across two domains: two medical data sets and two animal audio data sets with vocalizations represented as images (spectrograms). Results show that the proposed system’s performance competes competitively against the best-performing methods in the literature, obtaining state-of-the-art performance on one of the medical data sets, and does so without ad-hoc optimization of the clustering methods on the tested data sets.

scholarly journals miRNAome expression profiles in the gonads of adultMelopsittacus undulatus

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4615 ◽  
Author(s):  
Lan Jiang ◽  
Qingqing Wang ◽  
Jue Yu ◽  
Vinita Gowda ◽  
Gabriel Johnson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Early Development ◽  
Expression Profiles ◽  
Critical Role ◽  
Genomic Research ◽  
Go Annotation ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Mirnas Expression ◽  
Paired End Sequencing

The budgerigar (Melopsittacus undulatus) is one of the most widely studied parrot species, serving as an excellent animal model for behavior and neuroscience research. Until recently, it was unknown how sexual differences in the behavior, physiology, and development of organisms are regulated by differential gene expression. MicroRNAs (miRNAs) are endogenous short non-coding RNA molecules that can post-transcriptionally regulate gene expression and play a critical role in gonadal differentiation as well as early development of animals. However, very little is known about the role gonadal miRNAs play in the early development of birds. Research on the sex-biased expression of miRNAs in avian gonads are limited, and little is known aboutM. undulatus. In the current study, we sequenced two small non-coding RNA libraries made from the gonads of adult male and female budgerigars using Illumina paired-end sequencing technology. We obtained 254 known and 141 novel miRNAs, and randomly validated five miRNAs. Of these, three miRNAs were differentially expressed miRNAs and 18 miRNAs involved in sexual differentiation as determined by functional analysis with GO annotation and KEGG pathway analysis. In conclusion, this work is the first report of sex-biased miRNAs expression in the budgerigar, and provides additional sequences to the avian miRNAome database which will foster further functional genomic research.

scholarly journals Changes in antennal gene expression underlying sensory system maturation in Rhodnius prolixus

2021 ◽  
Author(s):  
Jose Manuel Latorre Estivalis ◽  
Ewald Grosse-Wilde ◽  
Gabriel R Fernandes ◽  
Bill S Hansson ◽  
Marcelo Gustavo Lorenzo
Keyword(s):  
Molecular Level ◽  
Expression Profiles ◽  
Sensory System ◽  
Transcript Abundance ◽  
Blood Feeding ◽  
Rhodnius Prolixus ◽  
Large Set ◽  
Illumina Platform ◽  
State Dependent ◽  
Host Cues

Background Triatomine bugs are the blood feeding insect vectors transmitting Chagas disease to humans, a neglected tropical disease that affects over 8 million people, mainly in Latin America. The behavioral responses to host cues and bug signals in Rhodnius prolixus are state dependent, i.e., they vary as a function of post-ecdysis age. At the molecular level, these changes in behavior are probably due to a modulation of peripheral and central processes. In the present study, we report a significant modulation of the expression of a large set of sensory-related genes. Results were generated by means of antennal transcriptomes of 5th instar larvae along the first week (days 0, 2, 4, 6 and 8) after ecdysis sequenced using the Illumina platform. Results Age induced significant changes in transcript abundance were established in more than 6,120 genes (54,7 % of 11,186 genes expressed) in the R. prolixus antenna. This was especially true between the first two days after ecdysis when more than 2,500 genes had their expression significantly altered. In contrast, expression profiles were almost identical between day 6 and 8, with only a few genes showing significant modulation of their expression. A total of 86 sensory receptors, odorant carriers and odorant degrading enzymes were significantly modulated across age points and clustered into three distinct expression profiles. Conclusions The set of sensory genes whose expression increased with age (profile 3) may include candidates underlying the increased responsiveness to host cues shown by R. prolixus during the first days after molting. For the first time, we describe the maturation process undergone at the molecular level by the peripheral sensory system is described in an hemimetabolous insect.

scholarly journals Increasing Productivity by Reducing Manufacturing Lead Time through Value Stream Mapping

2012 ◽  
pp. 225-229
Author(s):  
Renu Yadav ◽  
Ashish Shastri ◽  
Mithlesh Rathore
Keyword(s):  
Lead Time ◽  
Value Added ◽  
Value Stream Mapping ◽  
Mapping Technique ◽  
Inventory Level ◽  
Lead Times ◽  
Business World ◽  
Value Stream ◽  
Current State ◽  
Future State

To survive in today’s competitive business world, companies require small lead times, low costs and high customer service levels. As such, companies pay more effort to reduce their manufacturing lead times. Value stream mapping (VSM) technique has been used on a broad scale in big companies such as Toyota and Boeing. This paper considers the implementation of value stream mapping technique in manufacturing helical springs by railway spring manufacturing company. It focuses on product family, current state map improvements and the future state map. The aim is to identify waste in the form of non value added activities & processes and then removing them to improve the performance of the company. Current state map is prepared to describe the existing position and various problem areas.. Future state map is prepared to show the proposed improvement action plans. The achievements of value stream implementation are reduction in lead time, cycle time and inventory level. It was found that even a small company can make significant improvements by adopting VSM technology. It was concluded that if we adopt the VSM technique the company could reduce the manufacturing lead time from 36.86 days to 34.06 days.

Phenotypic Screen and Transcriptomics Approach Complement Each Other in Functional Genomics of Defensive Stink Gland Physiology

2021 ◽  
Author(s):  
Sabrina Lehmann ◽  
Bibi Atika ◽  
Daniela Grossmann ◽  
Christian Schmitt-Engel ◽  
Nadi Strohlein ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Large Scale ◽  
Reverse Genetics ◽  
Expression Profiles ◽  
Forward Genetics ◽  
Large Set ◽  
Knock Down ◽  
Genome Wide ◽  
Phenotypic Screen ◽  
A Genome

Abstract Background Functional genomics uses unbiased systematic genome-wide gene disruption or analyzes natural variations such as gene expression profiles of different tissues from multicellular organisms to link gene functions to particular phenotypes. Functional genomics approaches are of particular importance to identify large sets of genes that are specifically important for a particular biological process beyond known candidate genes, or when the process has not been studied with genetic methods before. Results Here, we present a large set of genes whose disruption interferes with the function of the odoriferous defensive stink glands of the red flour beetle Tribolium castaneum. This gene set is the result of a large-scale systematic phenotypic screen using a reverse genetics strategy based on RNA interference applied in a genome-wide forward genetics manner. In this first-pass screen, 130 genes were identified, of which 69 genes could be confirmed to cause knock-down gland phenotypes, which vary from necrotic tissue and irregular reservoir size to irregular color or separation of the secreted gland compounds. The knock-down of 13 genes caused specifically a strong reduction of para-benzoquinones, suggesting a specific function in the synthesis of these toxic compounds. Only 14 of the 69 confirmed gland genes are differentially overexpressed in stink gland tissue and thus could have been detected in a transcriptome-based analysis. Moreover, of the 29 previously transcriptomics-identified genes causing a gland phenotype, only one gene was recognized by this phenotypic screen despite the fact that 13 of them were covered by the screen. Conclusion Our results indicate the importance of combining diverse and independent methodologies to identify genes necessary for the function of a certain biological tissue, as the different approaches do not deliver redundant results but rather complement each other. The presented phenotypic screen together with a transcriptomics approach are now providing a set of close to hundred genes important for odoriferous defensive stink gland physiology in beetles.

Microarray analysis of Akt1 activation in transgenic mouse hearts reveals transcript expression profiles associated with compensatory hypertrophy and failure

2006 ◽  
Vol 27 (2) ◽  
pp. 156-170 ◽  
Author(s):  
Stephan Schiekofer ◽  
Ichiro Shiojima ◽  
Kaori Sato ◽  
Gennaro Galasso ◽  
Yuichi Oshima ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cardiac Hypertrophy ◽  
Molecular Mechanisms ◽  
Interstitial Fibrosis ◽  
Expression Profiles ◽  
Active Form ◽  
Heart Tissue ◽  
Compensatory Hypertrophy ◽  
Transcript Expression ◽  
Heart Size

To investigate molecular mechanisms involved in the development of cardiac hypertrophy and heart failure, we developed a tetracycline-regulated transgenic system to conditionally switch a constitutively active form of the Akt1 protein kinase on or off in the adult heart. Short-term activation (2 wk) of Akt1 resulted in completely reversible hypertrophy with maintained contractility. In contrast, chronic Akt1 activation (6 wk) induced extensive cardiac hypertrophy, severe contractile dysfunction, and massive interstitial fibrosis. The focus of this study was to create a transcript expression profile of the heart as it undergoes reversible Akt1-mediated hypertrophy and during the transition from compensated hypertrophy to heart failure. Heart tissue was analyzed before transgene induction, 2 wk after transgene induction, 2 wk of transgene induction followed by 2 days of repression, 6 wk after transgene induction, and 6 wk of transgene induction followed by 2 wk of repression. Acute overexpression of Akt1 (2 wk) leads to changes in the expression of 826 transcripts relative to noninduced hearts, whereas chronic induction (6 wk) led to changes in the expression of 1,611, of which 65% represented transcripts that were regulated during the pathological phase of heart growth. Another set of genes identified was uniquely regulated during heart regression but not growth, indicating that nonoverlapping transcription programs participate in the processes of cardiac hypertrophy and atrophy. These data define the gene regulatory programs downstream of Akt that control heart size and contribute to the transition from compensatory hypertrophy to heart failure.

scholarly journals Genome-Wide Analysis of the Role of NAC Family in Flower Development and Abiotic Stress Responses in Cleistogenes songorica

Genes ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 927
Author(s):  
Xifang Zong ◽  
Qi Yan ◽  
Fan Wu ◽  
Qian Ma ◽  
Jiyu Zhang
Keyword(s):  
Differential Expression ◽  
Stress Responses ◽  
Expression Profiles ◽  
Crop Improvement ◽  
Gene Expression Profiles ◽  
Purifying Selection ◽  
Go Annotation ◽  
Nac Transcription Factors ◽  
Response To Stress ◽  
Nac Family

Plant-specific NAC (NAM, ATAF, CUC) transcription factor (TF) family plays important roles in biological processes such as plant growth and response to stress. Nevertheless, no information is known about NAC TFs in Cleistogenes songorica, a prominent xerophyte desert grass in northwestern China. In this study, 162 NAC genes were found from the Cleistogenes songorica genome, among which 156 C. songoricaNAC (CsNAC) genes (96.3%) were mapped onto 20 chromosomes. The phylogenetic tree constructed by CsNAC and rice NAC TFs can be separated into 14 subfamilies. Syntenic and Ka/Ks analyses showed that CsNACs were primarily expanded by genomewide replication events, and purifying selection was the primary force driving the evolution of CsNAC family genes. The CsNAC gene expression profiles showed that 36 CsNAC genes showed differential expression between cleistogamous (CL) and chasmogamous (CH) flowers. One hundred and two CsNAC genes showed differential expression under heat, cold, drought, salt and ABA treatment. Twenty-three CsNAC genes were commonly differentially expressed both under stress responses and during dimorphic floret development. Gene Ontology (GO) annotation, coexpression network and qRT-PCR tests revealed that these CsNAC genes may simultaneously regulate dimorphic floret development and the response to stress. Our results may help to characterize the NAC transcription factors in C. songorica and provide new insights into the functional research and application of the NAC family in crop improvement, especially in dimorphic floret plants.

scholarly journals Overlapping protein-coding genes in human genome and their coincidental expression in tissues

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Chao-Hsin Chen ◽  
Chao-Yu Pan ◽  
Wen-chang Lin
Keyword(s):  
Human Genome ◽  
Expression Profiles ◽  
Tissue Expression ◽  
Human Protein ◽  
Clear Understanding ◽  
Overlapping Genes ◽  
Genome Sequences ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Overlapping Gene

Abstract The completion of human genome sequences and the advancement of next-generation sequencing technologies have engendered a clear understanding of all human genes. Overlapping genes are usually observed in compact genomes, such as those of bacteria and viruses. Notably, overlapping protein-coding genes do exist in human genome sequences. Accordingly, we used the current Ensembl gene annotations to identify overlapping human protein-coding genes. We analysed 19,200 well-annotated protein-coding genes and determined that 4,951 protein-coding genes overlapped with their adjacent genes. Approximately a quarter of all human protein-coding genes were overlapping genes. We observed different clusters of overlapping protein-coding genes, ranging from two genes (paired overlapping genes) to 22 genes. We also divided the paired overlapping protein-coding gene groups into four subtypes. We found that the divergent overlapping gene subtype had a stronger expression association than did the subtypes of 5ʹ-tandem overlapping and 3ʹ-tandem overlapping genes. The majority of paired overlapping genes exhibited comparable coincidental tissue expression profiles; however, a few overlapping gene pairs displayed distinctive tissue expression association patterns. In summary, we have carefully examined the genomic features and distributions about human overlapping protein-coding genes and found coincidental expression in tissues for most overlapping protein-coding genes.

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