IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2010
AbstractWe participated (as Team 9) in the Article Classification Task of the Biocreative II.5 C... more AbstractWe participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of full-text documents relevant for protein-protein interaction. We used two distinct classifiers for the online and offline challenges: (1) the ...
Background Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics da... more Background Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics data have been unevenly collected in different databases and published extensively in the literature. Without appropriate pharmacokinetics ontology and a well annotated pharmacokinetics corpus, it will be difficult to develop text mining tools for pharmacokinetics data collection from the literature and pharmacokinetics data integration from multiple databases. Description A comprehensive pharmacokinetics ontology was constructed. It can annotate all aspects of in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. It covers all drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK-corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three level annotatio...
Logical models offer a simple but powerful means to understand the complex dynamics of biochemica... more Logical models offer a simple but powerful means to understand the complex dynamics of biochemical regulation, without the need to estimate kinetic parameters. However, even simple automata components can lead to collective dynamics that are computationally intractable when aggregated into networks. In previous work we demonstrated that automata network models of biochemical regulation are highly canalizing, whereby many variable states and their groupings are redundant (Marques-Pita and Rocha, 2013). The precise charting and measurement of such canalization simplifies these models, making even very large networks amenable to analysis. Moreover, canalization plays an important role in the control, robustness, modularity and criticality of Boolean network dynamics, especially those used to model biochemical regulation (Gates and Rocha, 2016; Gates et al., 2016; Manicka, 2017). Here we describe a new publicly-available Python package that provides the necessary tools to extract, measu...
This paper presents our investigation on an agent-based model of Genotype Editing. This model is ... more This paper presents our investigation on an agent-based model of Genotype Editing. This model is based on several characteristics that are gleaned from the RNA editing system as observed in several organisms. The incorporation of editing mechanisms in an evolutionary agent-based model provides a means for evolving agents with heterogenous post-transcriptional processes. The study of this agent-based genotype-editing model has
Summary: We present a soft computing recommendation system named TalkMine, to advance adaptive we... more Summary: We present a soft computing recommendation system named TalkMine, to advance adaptive web and digital library technology. TalkMine leads different databases or websites to learn new and adapt existing keywords to the categories recognized by its communities of users. It uses distributed artificial intelligence algorithms and soft computing technology. TalkMine is currently being implemented for the research library of
In this paper I sketch a rough taxonomy of self-organization which may be of relevance in the stu... more In this paper I sketch a rough taxonomy of self-organization which may be of relevance in the study of cognitive and biological systems. I frame the problem both in terms of the language of second- order cybernetics as well as the language of current theories of self-organization and complexity. The goal of establishing such a taxonomy is to allow for a classification of different tools used both in Artificial Intelligence and Artificial Life, so that different aspects of cognitive and biological systems may be incorporated in more accurate models of such systems. In particular, I defend, on the one hand, that self-organization alone is not rich enough for our intended simulations, and on the other, that genetic selection in biology and symbolic representation in cognitive science alone leave out the very important (self-organizing) characteristics of particular embodiments of evolving and learning systems.
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2010
AbstractWe participated (as Team 9) in the Article Classification Task of the Biocreative II.5 C... more AbstractWe participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of full-text documents relevant for protein-protein interaction. We used two distinct classifiers for the online and offline challenges: (1) the ...
Background Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics da... more Background Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics data have been unevenly collected in different databases and published extensively in the literature. Without appropriate pharmacokinetics ontology and a well annotated pharmacokinetics corpus, it will be difficult to develop text mining tools for pharmacokinetics data collection from the literature and pharmacokinetics data integration from multiple databases. Description A comprehensive pharmacokinetics ontology was constructed. It can annotate all aspects of in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. It covers all drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK-corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three level annotatio...
Logical models offer a simple but powerful means to understand the complex dynamics of biochemica... more Logical models offer a simple but powerful means to understand the complex dynamics of biochemical regulation, without the need to estimate kinetic parameters. However, even simple automata components can lead to collective dynamics that are computationally intractable when aggregated into networks. In previous work we demonstrated that automata network models of biochemical regulation are highly canalizing, whereby many variable states and their groupings are redundant (Marques-Pita and Rocha, 2013). The precise charting and measurement of such canalization simplifies these models, making even very large networks amenable to analysis. Moreover, canalization plays an important role in the control, robustness, modularity and criticality of Boolean network dynamics, especially those used to model biochemical regulation (Gates and Rocha, 2016; Gates et al., 2016; Manicka, 2017). Here we describe a new publicly-available Python package that provides the necessary tools to extract, measu...
This paper presents our investigation on an agent-based model of Genotype Editing. This model is ... more This paper presents our investigation on an agent-based model of Genotype Editing. This model is based on several characteristics that are gleaned from the RNA editing system as observed in several organisms. The incorporation of editing mechanisms in an evolutionary agent-based model provides a means for evolving agents with heterogenous post-transcriptional processes. The study of this agent-based genotype-editing model has
Summary: We present a soft computing recommendation system named TalkMine, to advance adaptive we... more Summary: We present a soft computing recommendation system named TalkMine, to advance adaptive web and digital library technology. TalkMine leads different databases or websites to learn new and adapt existing keywords to the categories recognized by its communities of users. It uses distributed artificial intelligence algorithms and soft computing technology. TalkMine is currently being implemented for the research library of
In this paper I sketch a rough taxonomy of self-organization which may be of relevance in the stu... more In this paper I sketch a rough taxonomy of self-organization which may be of relevance in the study of cognitive and biological systems. I frame the problem both in terms of the language of second- order cybernetics as well as the language of current theories of self-organization and complexity. The goal of establishing such a taxonomy is to allow for a classification of different tools used both in Artificial Intelligence and Artificial Life, so that different aspects of cognitive and biological systems may be incorporated in more accurate models of such systems. In particular, I defend, on the one hand, that self-organization alone is not rich enough for our intended simulations, and on the other, that genetic selection in biology and symbolic representation in cognitive science alone leave out the very important (self-organizing) characteristics of particular embodiments of evolving and learning systems.
ACM Conference on Human Factors in Computing Systems Workshop on Interactive Systems in Health Care, May 4, 2019
Over two million people in the U.S. are living with epilepsy, which is one of most common chronic... more Over two million people in the U.S. are living with epilepsy, which is one of most common chronic neu-rological condition. They have experienced challenges such as quality of health care, care coordination, and risks of sudden unexpected death. People with epilepsy and their caregivers (PWEC) desire for more resources and improvement in self-management. Our goal is to develop a patient-centered web service for them. Before we develop it, we conducted a focus group study to understand their needs, concerns, contexts of health information management, and experiences. Our preliminary findings include: (1) information seeking for treatment and side effect, (2) information sharing challenges with families and caregivers, and (3) preference for personalization and tailored information. CCS CONCEPTS • Applied computing → Health care information systems; Health informatics; • Human-centered computing → Human computer interaction (HCI). INTRODUCTION Epilepsy is a chronic medical condition, which is one of the most common neurological diseases such as migraine, stroke, and Alzheimer's disease [3]. Over two million people in the U.S. are living with epilepsy [2]. Challenges of people with epilepsy include quality of care, care coordination, side effects, stigma, uncertainties of social situations, risks of sudden unexpected death, etc [1, 5]. PWEC desire to find more resources and services and improve their self-management [7]. Our research goal is to develop a patient-centered web service for PWEC which will improve PWEC's activation-the degree to which a person has the knowledge, skills, and confidence to manage epilepsy. Our research team will develop a personalized Automated User Resource Atheneum (myAURA) by integrating big data resources into a large-scale epilepsy knowledge graph that will fuel novel network inference methods to recommend and visualize relevant information in a personalized manner. However, before we develop the system, we conducted the first stage of our user study to understand PWEC's needs, concerns, contexts, and experiences in terms of health information management. We present preliminary results of this user study here.
Proceedings of the ACM on Human-Computer Interaction, Apr 2021
There are over three million people living with epilepsy in the U.S. People with epilepsy experie... more There are over three million people living with epilepsy in the U.S. People with epilepsy experience multiple daily challenges such as seizures, social isolation, social stigma, experience of physical and emotional symptoms, medication side effects, cognitive and memory deficits, care coordination difficulties, and risks of sudden unexpected death. In this work, we report findings collected from 3 focus groups of 11 people with epilepsy and caregivers and 10 follow-up questionnaires. We found that these participants feel that most people do not know how to deal with seizures. To improve others' abilities to respond safely and appropriately to someone having seizures, people with epilepsy and caregivers would like to share and educate the public about their epilepsy conditions, reduce common misconceptions about seizures and prevent associated stigma, and get first aid help from the public when needed. Considering social stigma, we propose design implications of future technologies for effective delivery of appropriate first aid care information to bystanders around individuals with epilepsy when they experience a seizure.
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