Gene models

Ovarian cancer (OC) is a gynecological malignancy tumor with high recurrence and mortality rates. Programmed cell death (PCD) is an essential regulator in cancer metabolism, whose functions are still unknown in OC. Therefore, it is vital to determine the prognostic value and therapy response of PCD-related genes in OC.

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This research aimed to create a robust signature with hypoxia-related genes to predict the prognosis of breast cancer patients. The function of hypoxia genes was further studied through cell line experiments.

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To explore the value of six machine learning models based on PET/CT radiomics combined with EGFR in predicting brain metastases of lung adenocarcinoma. Retrospectively collected 204 patients with lung adenocarcinoma who underwent PET/CT examination and EGFR gene detection before treatment from Cancer Hospital Affiliated to Shandong First Medical University in 2020.

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Peripheral T-cell lymphoma (PTCL) refers to a heterogenous group of T-cell neoplasms with poor treatment responses and survival times. Canine PTCL clinically and immunophenotypically resembles the most common human subtype, PTCL-not otherwise specified (PTCL-NOS), leading to interest in this canine disease as a naturally occurring model for human PTCL.

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Although substantial efforts have been made to build molecular biomarkers to predict radiation sensitivity, the ability to accurately stratify the patients is still limited. In this study, we aim to leverage large-scale radiogenomics datasets to build genomic predictors of radiation response using the integral of the radiation dose–response curve.

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Glycometabolism and lipid metabolism are critical in cancer metabolic reprogramming. The primary aim of this study was to develop a prognostic model incorporating glycometabolism and lipid metabolism-related genes (GLRGs) for accurate prognosis assessment in patients with endometrial carcinoma (EC).

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This study sought to investigate the prognostic value of basement membrane (BM)-associated gene expressions in oral cancer. Methods We harvested and integrated data on BM-associated genes (BMGs), the oral cancer transcriptome, and clinical information from public repositories. After identifying differentially expressed BMGs, we used Cox and Lasso regression analyses to create a BMG-based risk score for overall survival at various intervals.

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Single nucleotide polymorphisms (SNPs) are common in genes and can lead to dysregulation of gene expression in tissues, which can affect carcinogenesis. Many studies reporting the association between xeroderma pigmentosum group D (XPD) polymorphisms of rs13181 and rs1799793 with oral cancer risk, but with conflicting and inconclusive results.

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Colon cancer (CC) is a malignancy associated with significant morbidity and mortality within the gastrointestinal tract. Recurrence and metastasis are the main factors affecting the prognosis of CC patients undergoing radical surgery; consequently, we attempted to determine the impact of immunity-related genes.

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Papillary thyroid carcinoma (PTC) is the most frequent histological type of thyroid carcinoma. Although an increasing number of diagnostic methods have recently been developed, the diagnosis of a few nodules is still unsatisfactory. Therefore, the present study aimed to develop and validate a comprehensive prediction model to optimize the diagnosis of PTC.

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Copy-number alterations (CNAs) are a hallmark of cancer and can regulate cancer cell states via altered gene expression values. Herein, we have developed a copy-number impact (CNI) analysis method that quantifies the degree to which a gene expression value is impacted by CNAs and leveraged this analysis at the pathway level.

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This study aims to identify functionally relevant lncRNAs impacting OS proliferation and lipid metabolism and seeks to shed light on the upstream regulatory mechanisms governing lipogenic enzyme activity. Based on comprehensive bioinformatic analysis and the establishment of a risk model, we identified seven lncRNAs signifcantly associated with clinical characteristics and lipid metabolism-related genes in patients with OS.

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Ebook "Molecular and cellular biology of platelet formation: Implications in health and disease" gives a comprehensive insight into platelet biogenesis, platelet signal transduction, involvement of platelets in disease, the use of diverse animal models for platelet research and future perspectives in regard to platelet production and gene therapy. Being written by international experts, the book is a concise state-of-the art work in the field of platelet biogenesis, biology and research.

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Ebook "Modeling in systems biology: The petri net approach" aims to meet a challenge that previously has been largely avoided by the Petri net community. The community used to be content with the demonstration that Petri nets were able to simulate quite a large number of partial systems when their homogeneity permitted a rather restricted application of the Petri net methodology. The proof of principle used to say that Petri net models can simulate otherwise established theoretical descriptions.

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Ebook "Frontiers in computational and systems biology" consists of 19 chapters and covers a wide spectrum of topics. Described applications of an RNA structure sampling algorithm to the rational design of short interfering RNAs for gene silencing by RNA interference and to target identification for microRNAs that play important roles in posttranscriptional gene regulation.

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Ebook "Introduction to computational biology: An evolutionary approach" Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models.

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Ebook "Muscle gene therapy" will bring together the leaders in the field of muscle gene transfer to provide an updated overview on the progress of muscle gene therapy. It will also highlight important clinical applications of muscle gene therapy. The new knowledge on the immune response to viral vectors has added new insight in overcoming the immune obstacles. Most importantly, the field has finally moved from small experimental animal models to human patients.

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Cerebral amyloidosis, neuroinflammation, and tauopathy are key features of Alzheimer’s disease (AD), but interactions among these features remain poorly understood. Our previous multiscale molecular network models of AD revealed TYROBP as a key driver of an immune- and microglia-specific network that was robustly associated with AD pathophysiology.

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CRISPR/Cas9 has revolutionized cancer mouse models. Although loss-of-function genetics by CRISPR/Cas9 is wellestablished, generating gain-of-function alleles in somatic cancer models is still challenging because of the low efficiency of gene knock-in.

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Intrachromosomal triplications (TRP) can contribute to disease etiology via gene dosage effects, gene disruption, position effects, or fusion gene formation. Recently, post-zygotic de novo triplications adjacent to copynumber neutral genomic intervals with runs of homozygosity (ROH) have been shown to result in uniparental isodisomy (UPD).

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