Inference of Causal Networks from Time-Varying Transcriptome Data via Sparse Coding
نویسندگان
چکیده
منابع مشابه
Inference of Causal Networks from Time-Varying Transcriptome Data via Sparse Coding
Temporal analysis of genome-wide data can provide insights into the underlying mechanism of the biological processes in two ways. First, grouping the temporal data provides a richer, more robust representation of the underlying processes that are co-regulated. The net result is a significant dimensional reduction of the genome-wide array data into a smaller set of vocabularies for bioinformatic...
متن کاملSparse Coding of Time-varying Natural Images
We show how the principle of sparse coding may be applied to learn the forms of structure occurring in time-varying natural images. A sequence of images is described as a linear superposition of space-time functions , each of which is convolved with a time-varying coeecient signal. When a sparse, independent representation is sought over the coeecients, the basis functions that emerge are space...
متن کاملCausal Inference for Time-Varying Instructional Treatments
The authors propose a strategy for studying the effects of time-varying instructional treatments on repeatedly observed student achievement. This approach responds to three challenges: (a) The yearly reallocation of students to classrooms and teachers creates a complex structure of dependence among responses; (b) a child’s learning outcome under a certain treatment may depend on the treatment a...
متن کاملFast and Accurate Causal Inference from Time Series Data
Causal inference from time series data is a key problem in many fields, and new massive datasets have made it more critical than ever. Accuracy and speed are primary factors in choosing a causal inference method, as they determine which hypotheses can be tested, how much of the search space can be explored, and what decisions can be made based on the results. In this work we present a new causa...
متن کاملCoding Time-Varying Signals Using Sparse, Shift-Invariant Representations
A common way to represent a time series is to divide it into shortduration blocks, each of which is then represented by a set of basis functions. A limitation of this approach, however, is that the temporal alignment of the basis functions with the underlying structure in the time series is arbitrary. We present an algorithm for encoding a time series that does not require blocking the data. Th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLoS ONE
سال: 2012
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0042306