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RNA interference (RNAi) is an endogenous cellular process in which small double-stranded RNAs lead to the destruction of mRNAs with complementary nucleoside sequence. With the production of RNAi libraries, large-scale RNAi screening in…

New experimental methods make it possible to measure the expression levels of many genes, simultaneously, in snapshots from thousands or even millions of individual cells. Current approaches to analyze these experiments involve clustering…

Conversational Information Seeking (CIS) is a relatively new research area within conversational AI that attempts to seek information from end-users in order to understand and satisfy users' needs. If realized, such a system has…

Information Retrieval · Computer Science 2021-12-15 Manas Gaur , Kalpa Gunaratna , Vijay Srinivasan , Hongxia Jin

Cell type identification from single-cell transcriptomic data is a common goal of single-cell RNA sequencing (scRNAseq) data analysis. Neural networks have been employed to identify cell types from scRNAseq data with high performance.…

Genomics · Quantitative Biology 2020-05-11 Xishuang Dong , Shanta Chowdhury , Uboho Victor , Xiangfang Li , Lijun Qian

The interpretation of count data originating from the current generation of DNA sequencing platforms requires special attention. In particular, the per-sample library sizes often vary by orders of magnitude from the same sequencing run, and…

Quantitative Methods · Quantitative Biology 2015-06-17 Paul J. McMurdie , Susan Holmes

Magnetic resonance imaging (MRI) quality assessment is crucial for clinical decision-making, yet remains challenging due to data scarcity and protocol variability. Traditional approaches face fundamental trade-offs: signal-based methods…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Fankai Jia , Daisong Gan , Zhe Zhang , Zhaochi Wen , Chenchen Dan , Dong Liang , Haifeng Wang

Mixed-precision quantization (MPQ) suffers from the time-consuming process of searching the optimal bit-width allocation i.e., the policy) for each layer, especially when using large-scale datasets such as ISLVRC-2012. This limits the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-24 Chen Tang , Kai Ouyang , Zenghao Chai , Yunpeng Bai , Yuan Meng , Zhi Wang , Wenwu Zhu

Blind Image Quality Assessment (BIQA) has advanced significantly through deep learning, but the scarcity of large-scale labeled datasets remains a challenge. While synthetic data offers a promising solution, models trained on existing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Aobo Li , Jinjian Wu , Yongxu Liu , Leida Li , Weisheng Dong

Single-nucleus RNA sequencing (snRNA-seq) has significantly advanced our understanding of the disease etiology of neurodegenerative disorders. However, the low quality of specimens derived from postmortem brain tissues, combined with the…

Genomics · Quantitative Biology 2025-02-28 Gyutaek Oh , Baekgyu Choi , Seyoung Jin , Inkyung Jung , Jong Chul Ye

Quantitative assessment of the growth of biological organisms has produced many mathematical equations. Many efforts have been given on statistical identification of the correct growth model from experimental data. Every growth equation is…

Methodology · Statistics 2021-02-17 Md Aktar Ul Karim , Supriya Ramdas Bhagat , Amiya Ranjan Bhowmick

Computational complexity is a key limitation of genomic analyses. Thus, over the last 30 years, researchers have proposed numerous fast heuristic methods that provide computational relief. Comparing genomic sequences is one of the most…

Analysis of single-cell RNA sequencing data is often conducted through network projections such as coexpression networks, primarily due to the abundant availability of network analysis tools for downstream tasks. However, this approach has…

Quantitative Methods · Quantitative Biology 2025-12-24 Wan He , Daniel I. Bolnick , Samuel V. Scarpino , Tina Eliassi-Rad

Sequence set is a widely-used type of data source in a large variety of fields. A typical example is protein structure prediction, which takes an multiple sequence alignment (MSA) as input and aims to infer structural information from it.…

Biomolecules · Quantitative Biology 2019-06-27 Fusong Ju , Jianwei Zhu , Guozheng Wei , Qi Zhang , Shiwei Sun , Dongbo Bu

The past few decades have seen great leaps in technologies to analyze cells and tissues. Omics methods in particular now allow us unprecedented access to their the molecular composition where the base-level resolution of transcripts and…

Other Quantitative Biology · Quantitative Biology 2022-12-20 Ashika-Sita Jayanthy

In mass spectrometry based quantitative proteomics research, the emerging iTRAQ technique has been widely adopted for high throughput protein profiling, as it enables one to measure multiple samples simultaneously in one multiplex…

Applications · Statistics 2016-01-26 Lin S. Chen , Jiebiao Wang , Xianlong Wang , Pei Wang

In systems biology, it is common to measure biochemical entities at different levels of the same biological system. One of the central problems for the data fusion of such data sets is the heterogeneity of the data. This thesis discusses…

Genomics · Quantitative Biology 2019-08-27 Yipeng Song

Accurately inferring the root causes of disease from sequencing data can improve the discovery of novel therapeutic targets. However, existing root causal inference algorithms require perfectly measured continuous random variables. Single…

Genomics · Quantitative Biology 2023-07-12 Eric V. Strobl

Genomic data has become increasingly accessible to the general public with the advent of companies offering whole genome sequencing at a relatively low cost. However, their reports are not verifiable due to a lack of crucial details and…

We introduce Sashimi plots, a quantitative multi-sample visualization of mRNA sequencing reads aligned to gene annotations. Sashimi plots are made using alignments (stored in the SAM/BAM format) and gene model annotations (in GFF format),…

In cancer biomarker development, a key objective is to evaluate whether a new biomarker, when combined with an established one, improves early cancer detection compared to using the established biomarker alone. Incremental value is often…

Methodology · Statistics 2025-11-21 Indrila Ganguly , Ying Huang
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