Ranking & Metrics
Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.
Research Impact Score:1.80
Contributing Best Scientists:20
H5-index:
Papers published by Best Scientists19
Research Ranking (Computer Science)433
Research Ranking (Genetics and Molecular Biology)1
Research Ranking (Biology and Biochemistry)2
Research Ranking (Medicine)9
Conference Call for Papers
PSB will bring together top researchers from North America, the Asian Pacific nations, Europe and around the world to exchange research results and address open issues in all aspects of computational biology. PSB will provide a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. PSB intends to attract a balanced combination of computer scientists and biologists, presenting significant original research, demonstrating computer systems, and facilitating formal and informal discussions on topics of importance to computational biology.
To provide focus for the very broad area of biological computing, PSB is organized into a series of specific sessions. Each session will involve both formal research presentations and open discussion groups.
Digital health technology data in biocomputing: Research efforts and considerations for expanding access
Graph Representations and Algorithms in Biomedicine
Overcoming health disparities in precision medicine
Precision Medicine: Using computation and artificial intelligence to improve healthcare and public health
SALUD: Scalable Applications of cLinical risk Utility and preDiction
Towards Ethical Biomedical Informatics
Overview
Top Research Topics at Pacific Symposium on Biocomputing?
Computational biology (24.93%)
Artificial intelligence (18.16%)
Genetics (14.56%)
The conference covers a variety of subjects, including Computational biology, Artificial intelligence, Genetics, Data mining and Gene.
In addition to Computational biology research, it aims to explore topics under Genome-wide association study, Bioinformatics, Gene expression profiling, Genome and Disease.
The event explores topics in Artificial intelligence which can be helpful for research in disciplines like Natural language processing, Machine learning and Pattern recognition.
The main emphasis of the conference is the research on Genetics, emphasizing the topic of Single-nucleotide polymorphism.
The Data mining study tackled is a key component of adjacent topics in the area of Set (abstract data type).
Gene research is concerned with Gene expression in particular.
What are the most cited papers published at the conference?
REVEAL, A GENERAL REVERSE ENGINEERING ALGORITHM FOR INFERENCE OF GENETIC NETWORK ARCHITECTURES (859 citations)
Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. (854 citations)
The spectrum kernel: a string kernel for SVM protein classification. (851 citations)
Research areas of the most cited articles at Pacific Symposium on Biocomputing:
The conference papers generally zeroe in on subjects such as Artificial intelligence, Computational biology, Data mining, Gene and Machine learning.
The works on Artificial intelligence tackled in the published articles bring together disciplines like Natural language processing, Relation (database) and Pattern recognition.
The Data mining research presented in the published articles also delves into studies in intersecting subjects like
Set (abstract data type) which connect with Sequence,
Software which connect with Theoretical computer science..
What topics the last edition of the conference is best known for?
Gene
Artificial intelligence
DNA
The previous edition focused in particular on these issues:
The scientific interests tackled in Pacific Symposium on Biocomputing are Data science, Computational biology, Precision medicine, Data mining and Bioinformatics.
Some problems in Computational biology that were presented in Pacific Symposium on Biocomputing overlapped with concepts under RNA, Mutation, Mutation (genetic algorithm), Translational bioinformatics and Gene regulatory network.
Genome, Human genome, Biorepository, KEGG and Analytics are some topics wherein Precision medicine research discussed in Pacific Symposium on Biocomputing have an impact.
It explores issues in Data mining which can be linked to other research areas like Gold standard (test), Personalized medicine, Pairwise comparison, Bayes' theorem and String (computer science).
The studies on Bioinformatics discussed can also contribute to research in the domains of Text mining, Cancer and Disease.
Topics in Sensitivity (control systems) explored in the event were investigated in conjunction with research in Machine learning and Artificial intelligence.
The most cited articles from the last conference are:
Social media mining for public health monitoring and surveillance (81 citations)
PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA. (73 citations)
ONE-CLASS DETECTION OF CELL STATES IN TUMOR SUBTYPES. (39 citations)
Papers citation over time
A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
Research.com
Top authors and change over time
The top authors publishing at Pacific Symposium on Biocomputing (based on the number of publications) are:
Marylyn D. Ritchie (16 papers) published 5 papers at the last edition, 3 more than at the previous edition,
Russ B. Altman (13 papers) published 3 papers at the last edition the same number as at the previous edition,
Jason H. Moore (10 papers) published 1 paper at the last edition, 4 less than at the previous edition,
Dana C. Crawford (10 papers) published 3 papers at the last edition, 1 less than at the previous edition,
Sarah A. Pendergrass (8 papers) published 2 papers at the last edition the same number as at the previous edition.
The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.
Research.com
Top affiliations and change over time
Only papers with recognized affiliations are considered
The top affiliations publishing at Pacific Symposium on Biocomputing (based on the number of publications) are:
Stanford University (48 papers) published 11 papers at the last edition, 2 more than at the previous edition,
Vanderbilt University (18 papers) published 5 papers at the last edition, 2 more than at the previous edition,
Pennsylvania State University (16 papers) published 5 papers at the last edition, 1 more than at the previous edition,
Case Western Reserve University (14 papers) published 3 papers at the last edition the same number as at the previous edition,
Dartmouth College (13 papers) published 2 papers at the last edition, 4 less than at the previous edition.
The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.
Research.com
Publication chance based on affiliation
The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
Research.com
During the most recent 2016 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 54.55% were posted by at least one author from the top 10 institutions publishing at the conference. Another 5.45% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 14.55% of all publications and 25.45% were from other institutions.
Returning Authors Index
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.
Research.com
Returning Institution Index
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Research.com
The experience to innovation index
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).
Research.com
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
