Article
Multidisciplinary Sciences
Linhua Wang, Mirjana Maletic-Savatic, Zhandong Liu
Summary: Spatially resolved transcriptomics is a new technique for mapping transcriptional information within tissues. In this study, the authors present MIST, a computational tool that detects molecular regions and denoises missing gene expression values using region-specific imputation.
NATURE COMMUNICATIONS
(2022)
Article
Biology
Zuhier Awan, Nuha Alrayes, Zeenath Khan, Majid Almansouri, Abdul Ibrahim Hussain Bima, Haifa Almukadi, Hussam Ibrahim Kutbi, Preetha Jayasheela Shetty, Noor Ahmad Shaik, Babajan Banaganapalli
Summary: This study identified potential genetic biomarkers for familial hypercholesterolemia (FH) by studying the global gene expression profile of blood cells. Dysregulated expression of genes related to lipid homeostasis, immune responses, and cell adhesion molecules was found in FH patients. The involvement of dysregulated thyroid hormone and ErbB signaling pathways, as well as the enrichment of specific genes, were observed. The key hub genes JAK3, PLCG2, and ZEB2 were identified to contribute to inflammation and immune response related phenotypes. These findings provide insights into the immune dysregulation underlying atherosclerosis among FH patients and may contribute to the development of genomic medicine for cardiovascular diseases.
SAUDI JOURNAL OF BIOLOGICAL SCIENCES
(2022)
Article
Biochemical Research Methods
Britta Velten, Jana M. Braunger, Ricard Argelaguet, Damien Arnol, Jakob Wirbel, Danila Bredikhin, Georg Zeller, Oliver Stegle
Summary: MEFISTO is a flexible and versatile toolbox for modeling high-dimensional data with spatial or temporal dependencies, enabling spatio-temporally informed dimensionality reduction, interpolation, and separation of smooth and non-smooth patterns of variation. It can also integrate underlying patterns of variation in multiple related datasets in a data-driven manner.
Article
Multidisciplinary Sciences
Md Tauhidul Islam, Lei Xing
Summary: The authors develop a cartography strategy based on gene-gene interactions to transform high-dimensional gene expression data into a spatially configured genomap, enabling accurate deep pattern discovery. This approach presents significant challenges and opportunities in the field of single cell genomics for biomedical research. The unique cartography method captures gene interactions in the spatial configuration of genomaps, allowing for the extraction of deep genomic interaction features and the discovery of discriminative patterns in the data.
NATURE COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Kristina Lietz, Babak Saremi, Lena Wiese
Summary: This study developed a web application that simplifies the analysis of microarray data and allows for the comparison of results from different technologies and organisms. The application provides a convenient and customizable analysis process and allows users to gain further insights from existing study data.
BMC BIOINFORMATICS
(2023)
Article
Genetics & Heredity
Wei Vivian Li, Yanzeng Li
Summary: The study presents a method called scLink, which utilizes single-cell RNA sequencing technologies for gene co-expression network analysis. Through simulation and real data studies, the advantages of scLink in improving single-cell gene network analysis are demonstrated.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2021)
Article
Biotechnology & Applied Microbiology
Kayla A. Johnson, Arjun Krishnan
Summary: This study provides a comprehensive benchmarking and analysis of 36 different workflows for constructing coexpression networks from RNA-seq datasets. The results demonstrate that between-sample normalization has the biggest impact, with counts adjusted by size factors producing networks that most accurately recapitulate known gene functional relationships. The findings provide researchers with concrete recommendations for building accurate coexpression networks from RNA-seq datasets.
Article
Multidisciplinary Sciences
Chang Su, Zichun Xu, Xinning Shan, Biao Cai, Hongyu Zhao, Jingfei Zhang
Summary: The advancement of scRNA-seq technology enables the direct inference of co-expressions in specific cell types, but existing methods fail to address the challenges of sequencing depth variations and measurement errors. CS-CORE is a statistical approach that accurately estimates and tests cell-type-specific co-expressions while considering these challenges. Evaluations demonstrate that CS-CORE outperforms existing methods in terms of accuracy and identification of relevant co-expressions. Applied to scRNA-seq data from Alzheimer's disease and COVID-19 patients, CS-CORE identifies reproducible and biologically relevant cell-type-specific co-expressions and differential co-expressions.
NATURE COMMUNICATIONS
(2023)
Review
Fisheries
Mario Caruffo, Dinka Mandakovic, Pablo Cabrera, Igor Pacheco, Liliana Montt, Ignacio Chavez-Baez, Madelaine Mejias, Francisca Vera-Tamargo, Javiera Perez-Valenzuela, Alonso Carrasco-Labra, Rodrigo Pulgar
Summary: This systematic review analyzed the gene expression responses to infectious diseases in teleosts using various pathogens and provided insights into potential unknown functions related to fish infections, highlighting the importance of future research in this area.
REVIEWS IN AQUACULTURE
(2021)
Article
Biochemistry & Molecular Biology
Mengting Huang, Yixuan Yang, Xingzhao Wen, Weiqiang Xu, Na Lu, Xiao Sun, Jing Tu, Zuhong Lu
Summary: Although single cell RNA sequencing technologies are well developed, acquiring large-scale single cell expression data can still be costly. The study proposes a method of compressing expression profiles from the sample dimension by assigning each cell into multiple pools and demonstrates that expression profiles can be inferred from pool expression data with a overlapping pooling design and compressed sensing strategy. This approach, when combined with plate-based scRNA-seq measurement, maintains superior gene detection sensitivity and individual identity while reducing library costs by half.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Genetics & Heredity
Feng Jin, Lei Li, Yuehan Hao, Ling Tang, Yuye Wang, Zhiyi He
Summary: Through microarray and weighted gene co-expression network analysis, we identified four candidate blood mRNAs related to ICH, which showed different expression patterns in peripheral blood and perihematomal tissues at different time points and might affect the progression of ICH through neuroinflammation, cell apoptosis, and pyroptosis.
FRONTIERS IN GENETICS
(2021)
Article
Chemistry, Multidisciplinary
George I. Lambrou, Kleanthis Vichos, Dimitrios Koutsouris, Apostolos Zaravinos
Summary: Urinary bladder cancer (UBC) is the second most common urogenital solid tumor, with several new candidate prognostic markers identified. This study aimed to detect global gene co-expression profiles among a high number of UBC tumors, resulting in the identification of novel candidate markers and potential drugs for the disease.
APPLIED SCIENCES-BASEL
(2021)
Article
Multidisciplinary Sciences
Duc Tran, Hung Nguyen, Bang Tran, Carlo La Vecchia, Hung N. Luu, Tin Nguyen
Summary: Accurate analysis of single-cell RNA sequencing (scRNA-seq) data is crucial for various research fields, but is often hindered by technical noise and high dropout rates. The hierarchical autoencoder, scDHA, introduced in this study, outperforms existing methods in various aspects of scRNA-seq analysis, including cell segregation and classification.
NATURE COMMUNICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Soumen Kumar Pati, Ayan Banerjee, Sweta Manna
Summary: It is not feasible to investigate the whole genes at a microscopic level for disease classification in Genomics. Currently, a novel gene subset selection technique has been developed based on Heatmap Analysis and Graph Neural Network (HAGNN) to identify the most significant genes causing cancer. The proposed methodology outperformed the existing methods and has a greater impact on the advancement of the GNN-based gene selection.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Benjamin Allaert, Ioan Marius Bilasco, Chaabane Djeraba
Summary: In this paper, a new method for facial expression recognition is developed based on Local Motion Patterns (LMP) feature, which separates consistent motion patterns from noise. The method analyzes the elasticity and deformations of facial skin during expressions, and provides a unified approach for recognizing both macro and micro expressions. It also tackles challenges in in-the-wild expression recognition such as lighting variations and head pose changes.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2022)
Article
Computer Science, Information Systems
Debasish Das, Utpal Sharma, D. K. Bhattacharyya
INTERNATIONAL JOURNAL OF INFORMATION SECURITY
(2019)
Article
Biochemical Research Methods
Syed Sazzad Ahmed, Swarup Roy, Jugal Kalita
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2020)
Article
Biochemical Research Methods
Koyel Mandal, Rosy Sarmah, Dhruba Kumar Bhattacharyya
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2019)
Review
Biology
Tulika Kakati, Dhruba K. Bhattacharyya, Pankaj Barah, Jugal K. Kalita
COMPUTERS IN BIOLOGY AND MEDICINE
(2019)
Article
Computer Science, Artificial Intelligence
Keshab Nath, Swarup Roy, Sukumar Nandi
APPLIED SOFT COMPUTING
(2020)
Article
Genetics & Heredity
Jayanta Kumar Das, Antara Sengupta, Pabitra Pal Choudhury, Swarup Roy
Summary: In this study, a novel alignment-free method CoFASA was proposed for similarity analysis of nucleotide sequences by generating 20-dimensional features for phylogenetic analysis. Experimental assessments showed that CoFASA outperforms well-known alignment-free methods in predicting taxonomic relationships among candidate taxa.
Article
Computer Science, Artificial Intelligence
Hussain Ahmed Chowdhury, Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita
Summary: The study introduces a density-based clustering method UIFDBC that can detect clusters of arbitrary shapes without user input. Evaluation results show the method outperforms its counterparts in discovering arbitrary shaped clusters and has the ability to handle low-density instances.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Biochemical Research Methods
Koyel Mandal, Rosy Sarmah, Dhruba Kumar Bhattacharyya
Summary: The paper introduces the POPBic algorithm, incorporating KEGG pathways to discover genes with similar expression patterns based on pathway relationships. Experimental results demonstrate the algorithm's sensitivity and robustness in the presence of noise, confirming its ability to detect biologically significant biclusters.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Koyel Mandal, Rosy Sarmah, Dhruba Kumar Bhattacharyya
Summary: Exploratory analysis of high throughput gene sample time data plays a crucial role in biomedical and bioinformatics research, providing insights into gene regulatory mechanisms and hidden biological knowledge. In this study, a novel semi-supervised Pathway-based Order Preserving Triclustering algorithm is proposed to identify different types of triclusters. Experimental results on artificial and real datasets, including breast cancer and HIV data, demonstrate the effectiveness of the algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Biochemical Research Methods
Softya Sebastian, Swarup Roy, Jugal Kalita
Summary: Inference of large-scale gene regulatory networks is crucial for understanding gene interactions. Existing methods are limited to small networks, so parallel computing is proposed to construct large networks. A generic parallel framework is proposed which can infer large networks without re-engineering existing methods, and has been tested on various inference methods with good results. Finally, a gene network associated with Alzheimer's Disease was successfully inferred using the framework, revealing hub genes related to the disease.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Immunology
Giuseppe Tradigo, Jayanta Kumar Das, Patrizia Vizza, Swarup Roy, Pietro Hiram Guzzi, Pierangelo Veltri
Summary: This paper discusses the issues of vaccine diffusion and strategies for monitoring the pandemic. It describes the importance and take up of vaccines, as well as the links between vaccine procedures and the containment of COVID-19 variants and their long-term effects.
Article
Biology
Monica Jha, Swarup Roy, Jugal K. Kalita
COMPUTERS IN BIOLOGY AND MEDICINE
(2020)
Article
Remote Sensing
Dibyajyoti Chutia, Naiwrita Borah, Diganta Baruah, Dhruba Kumar Bhattacharyya, P. L. N. Raju, K. K. Sarma
Article
Telecommunications
Abdulaziz Alzubaidi, Swarup Roy, Jugal Kalita
DIGITAL COMMUNICATIONS AND NETWORKS
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Manaswita Saikia, Nazrul Hoque, Dhruba Kumar Bhattacharyya
RECENT DEVELOPMENTS IN MACHINE LEARNING AND DATA ANALYTICS
(2019)