Statistical physics and information theory perspectives on complex systems and networks

Complex physical, biological, and sociotehnical systems often display various phenomena that can't be understood using traditional tools of single disciplines. We describe work on developing and applying theoretical methods to understand phenomena of this type, using statistical physics, networks, spectral graph theory, information theory, and geometry. Financial systems--being highly stochastic, with agents in a complex environment--offer a unique arena to develop and test new ways of thinking about complexity. We develop a framework for analyzing market dynamics motivated by linear response theory, and propose a model based on agent behavior that naturally incorporates external influences. We investigate central issues such as price dynamics, processing and incorporation of information, and how agent behavior influences stability. We find that the mean field behavior of our model captures important aspects of return dynamics, and identify a stable-unstable regime transition depending on easily measurable model parameters. Our methods naturally connect external factors to internal market features and behaviors, and therefore address the crucial question of how system stability relates to agent behavior and external forces. Complex systems are often interconnected heterogeneously, with subunits influencing others counterintuitively due to specific details of their connections. Correlations are insufficient to characterize this due to, e.g., being symmetric and unable to discern directional relationships. We synthesize ideas from information and network theory to introduce a general tool for studying such relations in networks. Based on transfer entropy, we propose a measure--Effective Transfer Entropy Dependency--that measures influence by considering precisely how much of a source node's influence on targets is due to intermediates. We apply this to indices of the world's major markets, finding that our measure anticipates same-day correlation structure from lagged time-series data, and identifies influencers not found using standard correlations. Graphs are essential for understanding complex systems and datasets. We present new methods for identifying important structure in graphs, based on ideas from quantum information theory and statistical mechanics, and the renormalization group. We apply information geometry and spectral geometry to study the geometric structures that arise from graphs and random graph models, and suggest future extensions and applications to important problems like graph partitioning and machine learning.2020-04-22T00:00:00

Protein Binding Drug-Drug Interaction between Warfarin and Tizoxanide in Human Plasma

The goal of the in vitro research was to evaluate the potential for inhibition of warfarin protein binding by tizoxanide. Warfarin was of particular interest for the present investigation because it has been shown to be highly bound to plasma proteins and is a narrow therapeutic index drug. Tizoxanide is an active metabolite of an anti-infective prodrug nitazoxanide and also highly protein-bound medication. Both drugs are expected to be co-administered clinically. Protein binding of warfarin was investigated using a centrifugal ultrafiltration technique. Co-administration of tizoxanide significantly inhibited protein binding of warfarin for all concentrations tested. Tizoxanide increased free fraction (fu) of warfarin 34, 28, and 20-fold for concentration of 50, 75, and 100 μg/ml, respectively. The interaction could potentially result in increasing the toxicity of warfarin therapy and the risk of bleeding

High-complexity extracellular barcoding using a viral hemagglutinin

While single-cell sequencing technologies have revealed tissue heterogeneity, resolving mixed cellular libraries into cellular clones is essential for many pooled screens and clonal lineage tracing. Fluorescent proteins are limited in number, while DNA barcodes can only be read after cell lysis. To overcome these limitations, we used influenza virus hemagglutinins to engineer a genetically encoded cell-surface protein barcoding system. Using antibodies paired to hemagglutinins carrying combinations of escape mutations, we developed an exponential protein barcoding system which can label 128 clones using seven antibodies. This study provides a proof of principle for a strategy to create protein-level cell barcodes that can be used in vivo in mice to track clonal populations

Nontemplated Nucleotide Additions Distinguish the Small RNA Composition in Cells from Exosomes

Functional biomolecules, including small noncoding RNAs (ncRNAs), are released and transmitted between mammalian cells via extracellular vesicles (EVs), including endosome-derived exosomes. The small RNA composition in cells differs from exosomes, but underlying mechanisms have not been established. We generated small RNA profiles by RNA sequencing (RNA-seq) from a panel of human B cells and their secreted exosomes. A comprehensive bioinformatics and statistical analysis revealed nonrandomly distributed subsets of microRNA (miRNA) species between B cells and exosomes. Unexpectedly, 3′ end adenylated miRNAs are relatively enriched in cells, whereas 3′ end uridylated isoforms appear overrepresented in exosomes, as validated in naturally occurring EVs isolated from human urine samples. Collectively, our findings suggest that posttranscriptional modifications, notably 3′ end adenylation and uridylation, exert opposing effects that may contribute, at least in part, to direct ncRNA sorting into EVs.T.W. is supported by VIDI 91711366. D.M.P. is supported by personal Dutch Cancer Society research award (KWF-5510). This work was funded by AICR grant 11-0157 and NWO-VENI 91696087 awarded to D.M.P

CDD: a Conserved Domain Database for protein classification

The Conserved Domain Database (CDD) is the protein classification component of NCBI's Entrez query and retrieval system. CDD is linked to other Entrez databases such as Proteins, Taxonomy and PubMed®, and can be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=cdd. CD-Search, which is available at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, is a fast, interactive tool to identify conserved domains in new protein sequences. CD-Search results for protein sequences in Entrez are pre-computed to provide links between proteins and domain models, and computational annotation visible upon request. Protein–protein queries submitted to NCBI's BLAST search service at http://www.ncbi.nlm.nih.gov/BLAST are scanned for the presence of conserved domains by default. While CDD started out as essentially a mirror of publicly available domain alignment collections, such as SMART, Pfam and COG, we have continued an effort to update, and in some cases replace these models with domain hierarchies curated at the NCBI. Here, we report on the progress of the curation effort and associated improvements in the functionality of the CDD information retrieval system

In Vivo miRNA Decoy Screen Reveals miR-124a as a Suppressor of Melanoma Metastasis

Melanoma is a highly prevalent cancer with an increasing incidence worldwide and high metastatic potential. Brain metastasis is a major complication of the disease, as more than 50% of metastatic melanoma patients eventually develop intracranial disease. MicroRNAs (miRNAs) have been found to play an important role in the tumorigenicity of different cancers and have potential as markers of disease outcome. Identification of relevant miRNAs has generally stemmed from miRNA profiling studies of cells or tissues, but these approaches may have missed miRNAs with relevant functions that are expressed in subfractions of cancer cells. We performed an unbiased in vivo screen to identify miRNAs with potential functions as metastasis suppressors using a lentiviral library of miRNA decoys. Notably, we found that a significant fraction of melanomas that metastasized to the brain carried a decoy for miR-124a, a miRNA that is highly expressed in the brain/neurons. Additional loss- and gain-of-function in vivo validation studies confirmed miR-124a as a suppressor of melanoma metastasis and particularly of brain metastasis. miR-124a overexpression did not inhibit tumor growth in vivo, underscoring that miR-124a specifically controls processes required for melanoma metastatic growth, such as seeding and growth post-extravasation. Finally, we provide proof of principle of this miRNA as a promising therapeutic agent by showing its ability to impair metastatic growth of melanoma cells seeded in distal organs. Our efforts shed light on miR-124a as an antimetastatic agent, which could be leveraged therapeutically to impair metastatic growth and improve patient survival

CDD: specific functional annotation with the Conserved Domain Database

NCBI's Conserved Domain Database (CDD) is a collection of multiple sequence alignments and derived database search models, which represent protein domains conserved in molecular evolution. The collection can be accessed at http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml, and is also part of NCBI's Entrez query and retrieval system, cross-linked to numerous other resources. CDD provides annotation of domain footprints and conserved functional sites on protein sequences. Precalculated domain annotation can be retrieved for protein sequences tracked in NCBI's Entrez system, and CDD's collection of models can be queried with novel protein sequences via the CD-Search service at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi. Starting with the latest version of CDD, v2.14, information from redundant and homologous domain models is summarized at a superfamily level, and domain annotation on proteins is flagged as either ‘specific’ (identifying molecular function with high confidence) or as ‘non-specific’ (identifying superfamily membership only)

CDD: a Conserved Domain Database for the functional annotation of proteins

NCBI’s Conserved Domain Database (CDD) is a resource for the annotation of protein sequences with the location of conserved domain footprints, and functional sites inferred from these footprints. CDD includes manually curated domain models that make use of protein 3D structure to refine domain models and provide insights into sequence/structure/function relationships. Manually curated models are organized hierarchically if they describe domain families that are clearly related by common descent. As CDD also imports domain family models from a variety of external sources, it is a partially redundant collection. To simplify protein annotation, redundant models and models describing homologous families are clustered into superfamilies. By default, domain footprints are annotated with the corresponding superfamily designation, on top of which specific annotation may indicate high-confidence assignment of family membership. Pre-computed domain annotation is available for proteins in the Entrez/Protein dataset, and a novel interface, Batch CD-Search, allows the computation and download of annotation for large sets of protein queries. CDD can be accessed via http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml

Genetic alterations on chromosome 17p associated with response to radiotherapy in bulky cervical cancer

Chromosome 17 alterations are found in more cancers than those of any other chromosome, and frequently involve the p53 gene on 17p13. The aim of this study was to identify the correlations between the presence of loss of heterozygosity (LOH) and microsatellite instability (MI) on chromosome 17p13 in patients with cervical cancer and the patients’ response to radiotherapy. A total of 50 patients were treated with definitive radiotherapy. We performed biopsies and took specimens from the tumour and venous blood of all patients. Tumour and normal DNAs were analysed by polymerase chain reaction for genetic losses and instability at three polymorphic microsatellite loci mapped to 17p13. Nineteen of the 50 tumours (38%) displayed a genetic alteration (GA) on 17p13, 16 (32%) were found to have LOH, and three (6%) showed MI. The sizes of the tumours of the GA-positive patients were significantly greater than those of the GA-negative patients (P = 0.009). The mean tumour diameter of all patients was 6 ± 2.4 cm. We divided the patients into those with tumours smaller than 6 cm in diameter (n = 26) and those with tumours equal to or greater than 6 cm in diameter (n = 24). The former group survived significantly longer compared to the latter group (P = 0.0002). Among the patients with < 6 cm tumours, all six GA-positive patients are alive with no evidence of disease (NED), whereas of the 20 GA-negative patients, 18 have NED and two are alive with disease (AWD) or suffered cancer-caused death (CD). Thus, there was no correlation between GA and radiotherapy response in the tumours smaller than 6 cm. However, among the patients with ≥ 6 cm tumours, two of the GA-positive patients have NED and 11 are AWD/CD, whereas seven of the GA-negative patients have NED and four are AWD/CD. Among the patients with ≥ 6 cm tumours, the response to radiotherapy of the GA-positive patients were significantly poorer than those of the GA-negative patients (P = 0.02). In addition, the GA-negative patients survived significantly longer compared to the GA-positive patients (P = 0.026). The results of this study suggest that GA increases with tumour growth. Improved success in the management of bulky cervical cancer requires a better understanding of its biological behaviour. © 1999 Cancer Research Campaig