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At least 955 records · Page 53Linked to original sources
PubMed2006

Global mapping of pharmacological space.

We present the global mapping of pharmacological space by the integration of several vast sources of medicinal chemistry structure-activity relationships (SAR) data. Our comprehensive mapping of pharmacological space enables us to identify confidently the human targets for which chemical tools and drugs have been discovered to date. The integration of SAR data from diverse sources by unique canonical chemical structure, protein sequence and disease indication enables the construction of a ligand-target matrix to explore the global relationships between chemical structure and biological targets. Using the data matrix, we are able to catalog the links between proteins in chemical space as a polypharmacology interaction network. We demonstrate that probabilistic models can be used to predict pharmacology from a large knowledge base. The relationships between proteins, chemical structures and drug-like properties provide a framework for developing a probabilistic approach to drug discovery that can be exploited to increase research productivity.

Computational Biology↗
PubMed2003

FRET imaging.

Förster (or Fluorescence) Resonance Energy Transfer (FRET) is unique in generating fluorescence signals sensitive to molecular conformation, association, and separation in the 1-10 nm range. We introduce a revised photophysical framework for the phenomenon and provide a systematic catalog of FRET techniques adapted to imaging systems, including new approaches proposed as suitable prospects for implementation. Applications extending from a single molecule to live cells will benefit from multidimensional microscopy techniques, particularly those adapted for optical sectioning and incorporating new algorithms for resolving the component contributions to images of complex molecular systems.

Fluorescence Resonance Energy Transfer↗
PubMed2006

Systematic identification of human mitochondrial disease genes through integrative genomics.

The majority of inherited mitochondrial disorders are due to mutations not in the mitochondrial genome (mtDNA) but rather in the nuclear genes encoding proteins targeted to this organelle. Elucidation of the molecular basis for these disorders is limited because only half of the estimated 1,500 mitochondrial proteins have been identified. To systematically expand this catalog, we experimentally and computationally generated eight genome-scale data sets, each designed to provide clues as to mitochondrial localization: targeting sequence prediction, protein domain enrichment, presence of cis-regulatory motifs, yeast homology, ancestry, tandem-mass spectrometry, coexpression and transcriptional induction during mitochondrial biogenesis. Through an integrated analysis we expand the collection to 1,080 genes, which includes 368 novel predictions with a 10% estimated false prediction rate. By combining this expanded inventory with genetic intervals linked to disease, we have identified candidate genes for eight mitochondrial disorders, leading to the discovery of mutations in MPV17 that result in hepatic mtDNA depletion syndrome. The integrative approach promises to better define the role of mitochondria in both rare and common human diseases.

Base Sequence↗
PubMed2006

Multiple knockout analysis of genetic robustness in the yeast metabolic network.

Genetic robustness characterizes the constancy of the phenotype in face of heritable perturbations. Previous investigations have used comprehensive single and double gene knockouts to study gene essentiality and pairwise gene interactions in the yeast Saccharomyces cerevisiae. Here we conduct an in silico multiple knockout investigation of a flux balance analysis model of the yeast's metabolic network. Cataloging gene sets that provide mutual functional backup, we identify sets of up to eight interacting genes and characterize the 'k robustness' (the depth of backup interactions) of each gene. We find that 74% (360) of the metabolic genes participate in processes that are essential to growth in a standard laboratory environment, compared with only 13% previously found to be essential using single knockouts. The genes' k robustness is shown to be a solid indicator of their biological buffering capacity and is correlated with both the genes' environmental specificity and their evolutionary retention.

Computer Simulation↗
PubMed2007

Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database.

The past decade has witnessed hundreds of reports declaring or refuting genetic association with putative Alzheimer disease susceptibility genes. This wealth of information has become increasingly difficult to follow, much less interpret. We have created a publicly available, continuously updated database that comprehensively catalogs all genetic association studies in the field of Alzheimer disease (http://www.alzgene.org). We performed systematic meta-analyses for each polymorphism with available genotype data in at least three case-control samples. In addition to identifying the epsilon4 allele of APOE and related effects, we pinpointed over a dozen potential Alzheimer disease susceptibility genes (ACE, CHRNB2, CST3, ESR1, GAPDHS, IDE, MTHFR, NCSTN, PRNP, PSEN1, TF, TFAM and TNF) with statistically significant allelic summary odds ratios (ranging from 1.11-1.38 for risk alleles and 0.92-0.67 for protective alleles). Our database provides a powerful tool for deciphering the genetics of Alzheimer disease, and it serves as a potential model for tracking the most viable gene candidates in other genetically complex diseases.

Alzheimer Disease↗
PubMed2005

Kinomics: methods for deciphering the kinome.

Phosphorylation by protein kinases is the most widespread and well-studied signaling mechanism in eukaryotic cells. Phosphorylation can regulate almost every property of a protein and is involved in all fundamental cellular processes. Cataloging and understanding protein phosphorylation is no easy task: many kinases may be expressed in a cell, and one-third of all intracellular proteins may be phosphorylated, representing as many as 20,000 distinct phosphoprotein states. Defining the kinase complement of the human genome, the kinome, has provided an excellent starting point for understanding the scale of the problem. The kinome consists of 518 kinases, and every active protein kinase phosphorylates a distinct set of substrates in a regulated manner. Deciphering the complex network of phosphorylation-based signaling is necessary for a thorough and therapeutically applicable understanding of the functioning of a cell in physiological and pathological states. We review contemporary techniques for identifying physiological substrates of the protein kinases and studying phosphorylation in living cells.

Adenosine Triphosphate↗
PubMed2025

An atlas of ferroptosis-induced secretomes.

Cells undergoing regulated necrosis systemically communicate with the immune system via the release of protein and non-protein secretomes. Ferroptosis is a recently described iron-dependent type of regulated necrosis driven by massive lipid peroxidation. While membrane rupture occurs during ferroptosis, a comprehensive appraisal of ferroptotic secretomes and their potential biological activity has been lacking. Here, we apply a multi-omics approach to provide an atlas of ferroptosis-induced secretomes and reveal a novel function in macrophage priming. Proteins with assigned DAMP and innate immune system function, such as MIF, heat shock proteins (HSPs), and chaperones, were released from ferroptotic cells. Non-protein secretomes with assigned inflammatory function contained oxylipins as well as TCA- and methionine-cycle metabolites. Interestingly, incubation of bone marrow-derived macrophages (BMDMs) with ferroptotic supernatants induced transcriptional reprogramming consistent with priming. Indeed, exposure to ferroptotic supernatants enhanced LPS-induced cytokine production. These results define a catalog of ferroptosis-induced secretomes and identify a biological activity in macrophage priming with important implications for the fine-tuning of inflammatory processes.

Ferroptosis↗
PubMed2026

Elevation-structured viral ecological strategies along glacier-fed rivers on the Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau, a climate-vulnerable source of Asia's major rivers, harbors underexplored viral communities critical to ecosystem functions. By integrating 597 metagenomes from the Yangtze, Yellow, Lancang, and Yarlung Tsangpo rivers with 85 public available glacial metagenomes (Tibetan Glacier Genome and Gene catalog), we built the Glacier-to-River Virome Catalogue, encompassing 36,358 vOTUs and 897,250 viral protein clusters, to decode viral adaptation and ecological influence across elevation gradients. Our results reveal that high-altitude conditions favor viruses with elevated Guanine-Cytosine content, larger genomes and more cold-adaptation genes. A central finding is a systematic viral lifestyle shift from temperate in glaciated regions to lytic viruses downstream, accompanied with decline of pathogens carrying antibiotic resistance genes along the glacier-to-river gradients. Further, viral auxiliary metabolic genes transition from glacier nutrient scavenging (e.g., nitrogen and sulfur transporters) to downstream mineralization processes (e.g., denitrification) in plains highlights their role in biogeochemical cycling. These findings position viruses as pivotal regulators of microbial community structural and functional dynamics to glacier-to-river gradient change and biogeochemistry in the Qinghai-Tibet Plateau, providing critical insights into climate response in vulnerable Asian water towers.

Ice Cover↗
PubMed2026

Mechanisms underlying disease-causing variants in promoters and enhancers.

The study of human monogenic disorders has been a powerful tool for generating a deep understanding of protein function/dysfunction and for uncovering underlying biological mechanisms. Here we explore the insights that an expanding catalog of noncoding monogenic disease variants can provide into the functions of the noncoding genome. We focus on small genetic alterations (one to a few tens of base pairs) in cis-regulatory elements-promoters, enhancers and silencers-and their potential mechanisms of action, such as loss or gain of function. We discuss the challenges in determining pathogenicity for variants in the noncoding genome, discuss why there might be so few concrete examples and highlight the opportunities for advancing this area of human genetics by using experimental and machine-learning tools.

Journal Article↗
PubMed2026

Pan-genome-based resequencing of 2,320 accessions reveals structural variations and accelerates breeding advances in cultivated peanut.

The cultivated peanut is a crucial global legume crop that is essential for food security and nutrition, particularly in developing regions. However, its limited genetic variation hampers breeding progress and yield improvement. Here we constructed a graph-based pan-genome for peanut, incorporating 14 genomes that represent all 6 peanut varieties. Using this pan-genome, we genotyped 2,320 accessions, covering 88.03% of ICRISAT and 59.21% of USDA core germplasm, enriching valuable resources for genomic studies and breeding. We cataloged genomic structural variations and investigated the role of homoeologous exchanges in population divergence. Through our pan-genome approach, we overcame the challenges of genotyping posed by homoeologous exchanges and identified key genes associated with flowering and dwarfism in peanut. By integrating superior haplotypes and germplasm resources guided by the pan-genome, we further developed high-yield dwarf lines. This work provides essential genomic resources to accelerate functional gene discovery and modern peanut breeding.

Journal Article↗
PubMed2026

An integrated global resource of wetland microbiomes linking environmental metadata, community profiles, and genome-resolved metabolic traits.

Wetlands are biogeochemical hotspots pivotal to global carbon and nutrient cycling, yet genome-resolved studies across diverse wetland types remain limited. To address this, we constructed a global wetland metagenomic dataset, integrating environmental metadata, community profiles, and genome-resolved metabolic traits. This dataset comprises 1,962 samples-including 129 newly sequenced field-collected samples-from lakes, rivers, paddies, marshes, and coastal wetlands, spanning water, soil, and sediment habitats. We generated comprehensive taxonomic profiles for all 1,962 samples, and used 251 samples to reconstruct 5,704 sample-specific metagenome-assembled genomes (MAGs). These MAGs were subsequently dereplicated to establish a normalized, non-redundant catalog of 4,164 representative genomes. We further mapped gene repertoires to 549 KEGG modules to decode the metabolic potential of all 5,704 MAGs. This dataset depicts an overview of microbial genomic diversity across global wetlands and provides a comprehensive resource for understanding the metabolic capabilities, ecology, and evolution of wetland microbiomes.

Wetlands↗
PubMed2025

Association of cancers with the occurrence and 28-day mortality of sepsis: a mendelian randomization and mediator analysis.

Observational studies have indicated an association between cancer and the occurrence of sepsis, with an increased risk of mortality in cancer-related sepsis. However, whether a causal relationship exists between the two remains unknown. Summary statistics of thirteen cancers from the largest available genome-wide association studies (GWAS) of GWAS catalog and FinnGen biobank were extracted for the MR analysis. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. Univariable, multivariable, and reverse MR analyses were employed to explore potential associations between cancers and sepsis and its 28-day mortality. Moreover, a two-step mediation MR analysis was performed to investigate independent positive causal relationships between cancers and sepsis and its 28-day mortality. In univariable Mendelian randomization (MR) analysis, significant causal relationships were found between genetically predicted lung cancer (OR = 1.17, 95% CI = 1.08-1.26, adjusted p = 0.001), squamous cell lung carcinoma (OR = 1.10, 95% CI = 1.02-1.18, adjusted p = 0.042), lung adenocarcinoma (OR = 1.12, 95% CI = 1.03-1.21, adjusted p = 0.032), small cell lung carcinoma (OR = 1.07, 95% CI = 1.02-1.12, adjusted p = 0.031), and sepsis. Subsequent multivariable MR analysis revealed that these three types of lung cancer were independently associated with the risk of sepsis. Additionally, a causal relationship was found between lung cancer and 28-day mortality from sepsis, while no causal link was observed between non-solid tumors and the onset or death of sepsis. Reverse MR analysis did not indicate a potential for sepsis to trigger the onset of cancers. Furthermore, TRAIL was found to have promotive effects on the occurrence and mortality of sepsis. Lung cancer causally correlates with increased sepsis occurrence and 28-day mortality, as evidenced by Mendelian Randomization analysis. Genetic predispositions enhance this risk, underscoring the potential of genetic profiling to guide early, precise sepsis interventions in these patients.

Humans↗
PubMed2026

Automated segmentation and length measurement of metacarpal and phalangeal bones for hand radiograph evaluation.

Evaluating hand and wrist radiographs is essential in pediatric endocrinology and clinical genetics, particularly for the assessment of suspected skeletal anomalies. In this study, we present Auto-Bone-Caliper, an automated system for the segmentation and length measurement of metacarpal and phalangeal (M&P) bones, trained and evaluated on public datasets comprising both normal and dysmorphic cases. We first introduce InstanceSAM, a two-stage framework that detects and segments all 19 M&P bones in pediatric hand radiographs, achieving Dice scores of 98.7% for normal bones and 95.0% for dysmorphic bones. We further develop and evaluate three methods for bone-length estimation, identifying a k-means-based approach as the most accurate, with relative errors of 2.2% for normal bones and 4.5% for dysmorphic bones. Our automated pipeline, Auto-Bone-Caliper, integrates InstanceSAM with the k-means-based length-estimation method. To enable scale-independent downstream analyses, we derive relative bone-length measures from the automated measurements. Using these relative measures, we statistically compare measurements obtained using Auto-Bone-Caliper on an independent dataset with a healthy reference catalog of normal bone morphologies, observing a high level of agreement (Wasserstein-1 distance = 0.012). Finally, we demonstrate a potential clinical use case of Auto-Bone-Caliper by obtaining relative metacarpophalangeal pattern profiles for three genetic conditions, namely Turner syndrome, achondroplasia, and pseudohypoparathyroidism. Our results highlight the potential of the Auto-Bone-Caliper to streamline and standardize M&P length measurement, providing an objective and reproducible tool suitable for clinical application.

Humans↗
PubMed2022

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

Epidermal Growth Factor↗
PubMed2002

Genomics and medicine: hopes and challenges.

The major impact of the completion of the human genome sequence is the understanding of disease etiology with deduced therapy. The catalog of monogenic diseases should be easily completed through in silico cloning. The major challenge today is to decipher the polygenic and multifactorial etiology of common diseases, such as cancer, cardiovascular, nutritional, allergic, auto-immune, degenerative disorders. In fact every gene, when mutated, is a potential disease gene, and we end up with the new concept of 'reverse medicine', by which we will derive new morbid entities and pathogenic pathways from the knowledge of the structure and function of every gene. A new molecular and supramolecular integrated physiology will help build a molecular pathophysiology of the different syndromes, from which etiologic therapy will derive. The revolution in nosology, the problem of predictive medicine when therapeutic curative or preventive measure are lagging behind, are some of the novel challenges that molecular medicine has to face.

Costs and Cost Analysis↗
PubMed1999

Expression scanning of an array of growth control genes in human tumor cell lines.

Analysis of gene expression on a medium- or large-scale is an increasingly recognized method for functional and clinical investigations based on the now extensive catalog of known or partially sequenced genes. The accessibility of this approach can be enhanced by using readily available technology (macroarrays on Nylon, radioactive detection) and the IMAGE resource to assemble sets of targets. We have set up such a medium-scale, flexible system and validated it by the study of quantitative expression levels for 120 genes in six cell lines, including three mammary carcinoma cell lines. A number of important parameters are identified as necessary for the assembly of a valid set and the obtention of good-quality quantitative data. The extensive data assembled in this survey identified potential targets of carcinogenesis, for example the CRABP2 and GATA3 transcription factor genes. We also demonstrate the feasibility of this procedure for relatively small tumor samples, without recourse to probe amplification methods.

Breast Neoplasms↗
PubMed2000

The protein tyrosine kinase family of the human genome.

As the sequencing of the human genome is completed by the Human Genome Project, the analysis of this rich source of information will illuminate many areas in medicine and biology. The protein tyrosine kinases are a large multigene family with particular relevance to many human diseases, including cancer. A search of the human genome for tyrosine kinase coding elements identified several novel genes and enabled the creation of a nonredundant catalog of tyrosine kinase genes. Ninety unique kinase genes can be identified in the human genome, along with five pseudogenes. Of the 90 tyrosine kinases, 58 are receptor type, distributed into 20 subfamilies. The 32 nonreceptor tyrosine kinases can be placed in 10 subfamilies. Additionally, mouse orthologs can be identified for nearly all the human tyrosine kinases. The completion of the human tyrosine kinase family tree provides a framework for further advances in biomedical science.

Animals↗
PubMed2000

Gene expression in CD34(+) cells from normal bone marrow and leukemic origins.

INTRODUCTION: To address the molecular regulation of hematopoiesis and the complex mechanism in leukemogenesis, we established the first catalogs of genes expressed in normal bone marrow and leukemia CD34(+) cells. MATERIALS AND METHODS: CD34(+) cell cDNA libraries were constructed using mRNA from adult bone marrow and from a case of acute myeloid leukemia-M5 transformed from myelodysplastic syndrome (MDS-AML). Expressed sequence tags (ESTs) and full-length cDNAs were generated by sequencing and were annotated using bioinformatic tools. RESULTS: From a total of 4142 ESTs obtained from normal bone marrow, 3424 meaningful tags were integrated into 1630 clusters, representing 622 known genes, 522 dbEST entries and 486 novel sequences. Out of 5382 ESTs from MDS-AML, 1985 clusters were produced based on the analysis of 4321 useful ESTs, including 711 known genes, 657 known ESTs and 617 novel sequences. Among 251 transcripts found in both bone marrow and MDS-AML EST datasets and those present in only one dataset, 58 showed statistically significant differences in EST copy numbers between the two tissues (P<0.05). Twenty putative full-length cDNAs for novel genes were also cloned from the MDS-AML library. CONCLUSION: The distinct gene expression patterns in MDS-AML-CD34(+) cells as compared to normal control cells may contribute to the development and/or maintenance of the malignant phenotypes of leukemia cells.

Adult↗