Association of Metabolic and Endocrine Disorders with Bovine Ovarian Follicular Cysts.

After estrus, when mature follicles fail to ovulate, they may further develop to form follicular cysts, affecting the normal function of ovaries, reducing the reproductive efficiency of dairy cows and causing economic losses to cattle farms. However, the key points of ovarian follicular cysts pathogenesis remain largely unclear. The purpose of the current research was to analyze the formation mechanism of ovarian follicular cysts from hormone and gene expression profiles.

Identification of associations between lncRNA and drug resistance based on deep learning and attention mechanism.

Introduction: Abnormal lncRNA expression can lead to the resistance of tumor cells to anticancer drugs, which is a crucial factor leading to high cancer mortality. Studying the relationship between lncRNA and drug resistance becomes necessary. Recently, deep learning has achieved promising results in predicting biomolecular associations.

GAE-LGA: integration of multi-omics data with graph autoencoders to identify lncRNA-PCG associations.

Long non-coding RNAs (lncRNAs) can disrupt the biological functions of protein-coding genes (PCGs) to cause cancer. However, the relationship between lncRNAs and PCGs remains unclear and difficult to predict. Machine learning has achieved a satisfactory performance in association prediction, but to our knowledge, it is currently less used in lncRNA-PCG association prediction.

Relationship Between Skin Scales and the Main Flow Field Around the Shortfin Mako Shark .

The aim of this study was to reveal potential relationship between the main flow field around a shortfin mako shark and the surface morphology of shark skin. Firstly, a numerical simulation using the large eddy simulation (LES) method was conducted to obtain the main flow field around a smooth shark model. Then, the surface morphology characteristics of a shark () at different positions were characterized by scanning electron microscope (SEM), which showed that the morphology, riblet size, and density of scales at different positions on the shark were significantly different.

ImReLnc: Identifying Immune-Related LncRNA Characteristics in Human Cancers Based on Heuristic Correlation Optimization.

Long non-coding RNAs (lncRNAs) play critical roles in cancer through gene expression and immune regulation. Identifying immune-related lncRNA (irlncRNA) characteristics would contribute to dissecting the mechanism of cancer pathogenesis. Some computational methods have been proposed to identify irlncRNA characteristics in human cancers, but most of them are aimed at identifying irlncRNA characteristics in specific cancer.

Early pregnancy affects expression of Toll-like receptor signaling members in ovine spleen.

Toll-like receptors (TLRs) are involved to the maternal immune tolerance. The spleen is essential for adaptive immune reactions. However, it is unclear that early pregnancy regulates TLR-mediated signalings in the maternal spleen.

Linking genotype to phenotype in multi-omics data of small sample.

Background: Genome-wide association studies (GWAS) that link genotype to phenotype represent an effective means to associate an individual genetic background with a disease or trait. However, single-omics data only provide limited information on biological mechanisms, and it is necessary to improve the accuracy for predicting the biological association between genotype and phenotype by integrating multi-omics data. Typically, gene expression data are integrated to analyze the effect of single nucleotide polymorphisms (SNPs) on phenotype.

Comprehensive analyses of correlation and survival reveal informative lncRNA prognostic signatures in colon cancer.

Background: Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment.

Toll-like receptor signaling is changed in ovine lymph node during early pregnancy.

Toll-like receptors (TLRs) participate in regulation of adaptive immune responses, and lymph nodes play key roles in the initiation of immune responses. There is a tolerance to the allogenic fetus during pregnancy, but it is unclear that expression of TLR signaling is in ovine lymph node during early pregnancy. In this study, lymph nodes were sampled from day 16 of nonpregnant ewes and days 13, 16, and 25 of pregnant ewes, and the expressions of TLR family (TLR2, TLR3, TLR4, TLR5 and TLR9), adaptor proteins, including myeloid differentiation primary-response protein 88 (MyD88), tumor necrosis factor receptor associated factor 6 (TRAF6), and interleukin-1-receptor-associated kinase 1 (IRAK1), were analyzed through real-time quantitative polymerase chain reaction, Western blot, and immunohistochemistry analysis.

CONDEL: Detecting Copy Number Variation and Genotyping Deletion Zygosity from Single Tumor Samples Using Sequence Data.

Characterizing copy number variations (CNVs) from sequenced genomes is a both feasible and cost-effective way to search for driver genes in cancer diagnosis. A number of existing algorithms for CNV detection only explored part of the features underlying sequence data and copy number structures, resulting in limited performance. Here, we describe CONDEL, a method for detecting CNVs from single tumor samples using high-throughput sequence data.

SVSR: A Program to Simulate Structural Variations and Generate Sequencing Reads for Multiple Platforms.

Structural variation accounts for a major fraction of mutations in the human genome and confers susceptibility to complex diseases. Next generation sequencing along with the rapid development of computational methods provides a cost-effective procedure to detect such variations. Simulation of structural variations and sequencing reads with real characteristics is essential for benchmarking the computational methods.