Statistical analysis of genomic protein family and domain controlled annotations for functional investigation of classified gene lists

<p>Abstract</p> <p>Background</p> <p>The increasing protein family and domain based annotations constitute important information to understand protein functions and gain insight into relations among their codifying genes. To allow analyzing of gene proteomic annotations, we implemented novel modules within <it>GFINDer</it>, a Web system we previously developed that dynamically aggregates functional and phenotypic annotations of user-uploaded gene lists and allows performing their statistical analysis and mining.</p> <p>Results</p> <p>Exploiting protein information in Pfam and InterPro databanks, we developed and added in <it>GFINDer </it>original modules specifically devoted to the exploration and analysis of functional signatures of gene protein products. They allow annotating numerous user-classified nucleotide sequence identifiers with controlled information on related protein families, domains and functional sites, classifying them according to such protein annotation categories, and statistically analyzing the obtained classifications. In particular, when uploaded nucleotide sequence identifiers are subdivided in classes, the <it>Statistics Protein Families&Domains </it>module allows estimating relevance of Pfam or InterPro controlled annotations for the uploaded genes by highlighting protein signatures significantly more represented within user-defined classes of genes. In addition, the <it>Logistic Regression </it>module allows identifying protein functional signatures that better explain the considered gene classification.</p> <p>Conclusion</p> <p>Novel <it>GFINDer </it>modules provide genomic protein family and domain analyses supporting better functional interpretation of gene classes, for instance defined through statistical and clustering analyses of gene expression results from microarray experiments. They can hence help understanding fundamental biological processes and complex cellular mechanisms influenced by protein domain composition, and contribute to unveil new biomedical knowledge about the codifying genes.</p

MicroGen: a MIAME compliant web system for microarray experiment information and workflow management

BACKGROUND: Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. RESULTS: We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME) standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. CONCLUSION: MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production

A connecting system for cardiological lexicons

The purpose of this paper is to present the approach and the development of a software application ("lexicons connecting" system) to correlate effectively and unambiguously the correspondence between the specialist medical vocabulary and the familiar medical vocabulary for the cardiovascular domain. To investigate the question, the idea, the design, and the implementation of such system will be described. To this end, firstly, a number of research methodologies will be examined including domain ontologies development, database design and implementation. Then, the following implementation methodology and its results are presented. Finally, an example of the application use will be depicted and future work will be briefly described

Inherited disorder phenotypes: controlled annotation and statistical analysis for knowledge mining from gene lists

BACKGROUND: Analysis of inherited diseases and their associated phenotypes is of great importance to gain knowledge of underlying genetic interactions and could ultimately give clinically useful insights into disease processes, including complex diseases influenced by multiple genetic loci. Nevertheless, to date few computational contributions have been proposed for this purpose, mainly due to lack of controlled clinical information easily accessible and structured for computational genome-wise analyses. To allow performing phenotype analyses of inherited disorder related genes we implemented new original modules within GFINDer , a Web system we previously developed that dynamically aggregates functional annotations of user uploaded gene lists and allows performing their statistical analysis and mining. RESULTS: New GFINDer modules allow annotating large numbers of user classified biomolecular sequence identifiers with morbidity and clinical information, classifying them according to genetic disease phenotypes and their locations of occurrence, and statistically analyzing the obtained classifications. To achieve this we exploited, normalized and structured the information present in textual form in the Clinical Synopsis sections of the Online Mendelian Inheritance in Man (OMIM) databank. Such valuable information delineates numerous signs and symptoms accompanying many genetic diseases and it is divided into phenotype location categories, either by organ system or type of finding. CONCLUSION: Supporting phenotype analyses of inherited diseases and biomolecular functional evaluations, GFINDer facilitates a genomic approach to the understanding of fundamental biological processes and complex cellular mechanisms underlying patho-physiological phenotypes

Advising patients on selecting trustful apps for diabetes self-care

BACKGROUND: There has been a dramatic increase in mobile apps for diabetes self-care. However, their quality is not guaranteed and patients do not have the appropriate tools for careful evaluation. OBJECTIVE: This work aims to propose a tool to help patients with diabetes select an appropriate app for self-care. METHODS: After identifying the conceptual framework of diabetes self-care, we searched Apple US app store and reviewed diabetes self-care apps, considering both generic and diabetes-specific features. Based on an existing tool for representing the benefits and weaknesses of medical apps, we created the pictorial identification schema/Diabetes Self-care tool, which specifically identified medical apps in the diabetes domain. RESULTS: Of the 952 apps retrieved, 67 were for diabetes self-care, while 26 were excluded because they were not updated in the last 12 months. Of the remaining 41, none cost more than 15 USD, and 36 implemented manual data entry. Basic features (data logging, data representation, and data delivery) were implemented in almost all apps, whereas advanced features (e.g., insulin calculator) were implemented in a small percentage of apps. The pictorial identification schema for diabetes was completed by one patient and one software developer for 13 apps. Both users highlighted weaknesses related to the functionalities offered and to their interface, but the patient focused on usability, whereas the software developer focused on technical implementation. CONCLUSIONS: The Pictorial Identification Schema/Diabetes Self-care is a promising graphical tool for perceiving the weaknesses and benefits of a diabetes self-care app that includes multiple user profile perspectives

Web-based telemonitoring and delivery of caregiver support for patients with Parkinson disease after deep brain stimulation: protocol

The increasing number of patients, the high costs of management, and the chronic progress of the disease that prevents patients from performing even simple daily activities make Parkinson disease (PD) a complex pathology with a high impact on society. In particular, patients implanted with deep brain stimulation (DBS) electrodes face a highly fragile stabilization period, requiring specific support at home. However, DBS patients are followed usually by untrained personnel (caregivers or family), without specific care pathways and supporting systems

eHealth Turning Points as Forced by the Covid-19 Dramatic Experience.

In this ongoing fall of the year 2021, many disciplines are frightened by the Covid-19 situation. A generalized sense of Scientific and administrative impotence, – in keeping the pandemic under real control, – is felt widely in Society. In this Invited Lecture the author reminds us of the blows suffered, recalls pertinent elements present in our social organization, browses selected eHealth experiences and proposes an open agenda of actions to allow the eHealth to help the population segments better, and individuals as well

A Manifesto on Telehealth and Telemedicine

An evident contrast exists between the generally easy way medical doctors and administrators use the term “telemedicine” and the wide variety of significantly different technologic methods and devices necessary for correctly performing specific tasks in the field. Many misunderstandings could be avoided by agreeing on the types of services that telemedicine can provide, names for those services, and descriptions of what is included in the services. This manifesto lists representative services, with a proposed name for and description of each