Problem Definition and Terminology Clause Samples
The Problem Definition and Terminology clause establishes the scope of the issue being addressed and provides clear definitions for key terms used throughout the agreement or document. This clause typically outlines the specific problem or subject matter that the parties intend to resolve, and lists important words or phrases with their precise meanings to avoid ambiguity. By doing so, it ensures that all parties share a common understanding of the context and language, which helps prevent misunderstandings and disputes over interpretation.
Problem Definition and Terminology. A phylogenetic network is a connected, rooted, simple, directed acyclic graph in which: (1) each node has outdegree at most 2; (2) each node has indegree 1 or 2, except the root node which has indegree 0; (3) no node has both indegree 1 and outdegree 1; and (4) all nodes with outdegree 0 are labeled by elements from a finite set L in such a way that no two nodes are assigned the same label. From here on, nodes of outdegree 0 are referred to as leaves and identified with their corresponding elements in L. We denote the set of all nodes and the set of leaves in a phylogenetic network N by V (N ) and Λ(N ), respectively. | Given a phylogenetic network N and a set L′, the topological restriction of N to L′, denoted by N L′, is defined as the phylogenetic network obtained by first deleting all nodes which are not on any directed path from the root to a leaf in L′ along with their incident edges, and then, for every node with outdegree 1 and indegree less than 2, contracting its outgoing edge (any resulting set of multiple edges between two nodes is replaced by a single edge). network of is a phylogenetic network A such that Λ(A) i∈N Λ(N ) and N ⊆ Given a set N = {N1,..., Nk} of phylogenetic networks, an agreement sub- ∈ N | for every Ni , A is isomorphic to a subgraph of Ni Λ(A) in which zero or more of the edges have been deleted and each outgoing edge from a node with 1 To evaluate a construction method , repeat the following steps a number of times. First, randomly generate a network N and evolve a sequence down the edges of N ac- cording to some chosen model of evolution, then build a network N' for the resulting set of sequences using M, and finally measure the similarity between N' and N . uL